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At least 55 records · Page 3

XRF-XFS-XAS-Auto v1.0 - Beta release

This software allows to analyze XRF maps, XFS spectra and XAS spectra collected at the Advanced Light Source's Beamline 10.3.2. Features include: 1) XRF maps: - process XRF maps, all elemental maps are saved as bmp automatically and labeled with the incident energy used, the scale bar is also labeled and can be controlled. - XRF elemental correlation plots, save the correlation plots automatically - Extract single or multiple transects in XRF maps on one or several regions of interest, each transect profile is numbered and saved in a corresponding folder, along with the corresponding maps showing transect location. 2) XFS spectra - save in log10 scale the XFS spectra, either a single or multiple files all at once. The files are saved as .bmp. - XFS spectra are labeled according to tabulated fluorescence emission lines. 3) XAS spectra - allows to plot individual scalers in the raw data. - allows calibration of the spectra using an Io internal glitch present in all spectra and performing 1st derivative. - Least-square linear combination fitting of XANES or extended XANES spectra using a database of standards using 1, 2 or 3 components maximum. It also provides the 5 top combinations and provide the user for the possibility of saving the 2nd, 3rd, 4th and 5th best combinations in addition to the best one. The processed spectra (pre-edge background substracted, post-edge normalized), the fits and residuals are automatically saved. A table of the component, with fit% and SSN is provided and saved automatically as well.

Fakra, Sirine↗

Investigations of element spatial correlation in Mn-promoted Co-based Fischer–Tropsch synthesis catalysts

Making connections between performance and structure in bimetallic catalysts requires knowledge of how the two elements are spatially associated. Elemental maps obtained by analytical TEM methods are an invaluable tool for identifying the location of different elements, but for many samples, visual inspection of elemental maps is insufficient for assessing the degree of element spatial correlation. This is particularly true for beam-sensitive materials where short mapping acquisition times lead to images with high noise and low color depth. In these situations, statistical analysis of elemental maps can be used to identify spatial correlations among the elements in a sample. In this work, the relationship between catalyst performance and bimetallic spatial association was explored using Mn-promoted Co-based Fischer-Tropsch synthesis catalysts prepared by different pretreatment methods. Mn was used as a catalyst additive to suppress methane formation. Catalysts that underwent calcination before reduction produced more methane and fewer long-chain hydrocarbons than catalysts that were directly reduced. The extent to which Co and Mn were spatially associated was assessed using correlation metrics, colocation plots, and histograms generated using data from STEM-EDS maps. Although both catalysts yielded visually similar elemental maps, the results of statistical analysis suggested that the calcined catalyst exhibited greater spatial segregation between the Co and Mn. These findings support the hypothesis that having Mn in close proximity to the Co is essential for the manifestation of Mn promotion effects in Co-based FTS catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

For a Few Howardites More: Grand Maps the Elemental Composition of Vesta

Dawn?s Gamma Ray and Neutron Detector (GRaND) successfully completed Low Altitude Mapping Orbit (LAMO) at Vesta. Over four months were spent acquiring data in a 460-km radius orbit around Vesta (265-km mean radius). In LAMO, strong signatures from Vesta were observed for gamma rays and neutrons. We present preliminary abundances, detection limits, and global maps of the elemental composition of Vesta.

Prettman, T.↗

Visualization of Current and Mapping of Elements in Quantum Dot Solar Cells

The delicate influence of properties such as high surface state density and organic-inorganic boundaries on the individual quantum dot electronic structure complicates pursuits toward forming quantitative models of quantum dot thin films ab initio. Our report describes the application of electron beam-induced current (EBIC) microscopy to depleted-heterojunction colloidal quantum dot photovoltaics (DH-CQD PVs), a technique which affords one a map of current production within the active layer of a PV device. The effects of QD sample size polydispersity as well as layer thickness in CQD active layers as they pertain to current production within these PVs are imaged and explained. The results from these experiments compare well with previous estimations, and confirm the ability of EBIC to function as a valuable empirical tool for the design and betterment of DH-CQD PVs. Lastly, extensive and unexpected PbS QD penetration into the mesoporous TiO 2 layer is observed through imaging of device cross sections by energy-dispersive X-ray spectroscopy combined with scanning transmission electron microscopy. Finally, the effects of this finding are discussed and corroborated with the EBIC studies on similar devices.

14 SOLAR ENERGY↗

Compressive Classification for TEM-EELS

Acquiring atomic-resolution images of beam sensitive materials or under dynamic conditions (e.g. operando STEM) is very difficult and requires precise dose fractioning to minimize the dose delivered to the sample and acquire the data more rapidly than dynamics present. Typical methods of low-dose STEM imaging include adjusting the beam current, dwell-time, and probe Scanning transmission electron microscopy (STEM) is used routinely to obtain atomic-resolution images of a small selection of radiation tolerant materials under stable conditions.size. All three of these determine the dose over a spatial area in STEM. Recently, compressive sensing [1] has been applied to electron microscopy. The computational imaging method of inpainting [2] has been proposed as a method to reduce dose and increase acquisition speed for STEM. Inpainting is a technique to recover missing pixels in an image. By skipping pixels (randomly) during acquisition, a fourth dose-control mechanism is realized [3]. A few implementations of randomly-subsampled STEM exist (e.g., [4]). To make the concepts of compressive sensing accessible to the microscopy community we begin with an example using atomic resolution images of a GaAs crystal (see Figure 1). Because the crystal is periodic it has a sparse representation in reciprocal space. In fact, a sparse representation is a key component of compressive sensing. If an image is sub-sampled randomly we find that the Fourier transform remains sparse, but becomes increasing noisy as less and less data is acquired. Yet, by finding the peaks in the reciprocal image and removing the noise it is possible to recover atomic resolution images with only 1% of the pixels. Figure 1 shows the reconstruction process for GaAs sub-sampled at 50%, 10%, 5%, and 1%. Periodic images form a special class for which the optimal sampling approach (according to CS theory) is a random selection of pixels. For non-periodic images, such as those arising in in-situ STEM, methods such as dictionary learning are necessary [2,5]. The data can be compressed in time for TEM [5] or pixels can be skipped randomly for STEM. There are several issues that arise in developing a random scan for STEM [4] and a coded aperture for TEM. The remainder of the talk will address these issues. References: [1] E Candes and M Wakin. Signal Processing Magazine, IEEE. 2(25) (2008), pp. 21. [2] A Stevens, Pu Y, Sun Y, et al. Artificial Intelligence & Statistics (AISTATS), 2017. [3] A Stevens, H Yang, L Carin et al. Microscopy 63(1), (2014), pp. 41. [4] L Kovarik, A Stevens, A Liyu et al. Appl. Phys. Lett. 109, 164102 (2016). [5] A Stevens, L Kovarik, P Abellan et al. Adv. Structural and Chemical Imaging 1(10), (2015), pp. 1. [6] Supported by the Chemical Imaging, Signature Discovery, and Analytics in Motion Initiatives at PNNL. PNNL is operated by Battelle Memorial Inst. for the US DOE; contract DE-AC05-76RL01830.

Hao, Weituo↗

Full Field X-Ray Fluorescence Imaging Using Micro Pore Optics for Planetary Surface Exploration

Many planetary surface processes leave evidence as small features in the sub-millimetre scale. Current planetary X-ray fluorescence spectrometers lack the spatial resolution to analyse such small features as they only provide global analyses of areas greater than 100 mm(exp 2). A micro-XRF spectrometer will be deployed on the NASA Mars 2020 rover to analyse spots as small as 120m. When using its line-scanning capacity combined to perpendicular scanning by the rover arm, elemental maps can be generated. We present a new instrument that provides full-field XRF imaging, alleviating the need for precise positioning and scanning mechanisms. The Mapping X-ray Fluorescence Spectrometer - "Map-X" - will allow elemental imaging with approximately 100μm spatial resolution and simultaneously provide elemental chemistry at the scale where many relict physical, chemical and biological features can be imaged in ancient rocks. The arm-mounted Map-X instrument is placed directly on the surface of an object and held in a fixed position during measurements. A 25x25 mm(exp 2) surface area is uniformly illuminated with X-rays or alpha-particles and gamma-rays. A novel Micro Pore Optic focusses a fraction of the emitted X-ray fluorescence onto a CCD operated at a few frames per second. On board processing allows measuring the energy and coordinates of each X-ray photon collected. Large sets of frames are reduced into 2d histograms used to compute higher level data products such as elemental maps and XRF spectra from selected regions of interest. XRF spectra are processed on the ground to further determine quantitative elemental compositions. The instrument development will be presented with an emphasis on the characterization and modelling of the X-ray focussing Micro Pore Optic. An outlook on possible alternative XRF imaging applications will be discussed.

micro-XRF spectrometer↗

Characterization of Fuel Cladding Chemical Interaction on a High Burnup U-10Zr Metallic Fuel via Electron Energy Loss Spectroscopy Enhanced by Machine Learning

Fuel cladding chemical interaction (FCCI) is one of the main performance limiting factors for metallic nuclear fuels. The interaction destabilizes the martensitic microstructure and deteriorates mechanical properties of HT-9 cladding. The detection of low atomic number elements (Z<10) and overlapping of elemental peaks can be problematic in interpreting energy dispersive X-ray spectroscopy (EDS) data. Electron energy loss spectroscopy (EELS) provides precise elemental edge energy values and can detect elements with a low atomic number. This work utilizes EELS to study the distribution of lanthanides and light elements at the interaction region. The sample was prepared from the FCCI region of a U-10Zr (wt.%) solid fuel with HT-9 cladding, irradiated to a burnup of 13.2 at.%. Processing the EELS data included three major steps: 1) enhance the signal to noise ratio by denoising the spectrum with principal component analysis (PCA) method, removing background and performing deconvolution; 2) identify chemical elements with core energy loss edges; 3) confirm different phases using a popular machine learning method, K-means. This work presents qualitative assessment of lanthanides and light elements like carbon (C) and oxygen (O) enhanced by the application of machine learning algorithms. By comparing with EDS elemental maps, EELS provides higher resolution chemical maps, reveals the distribution of carbon at the interaction region supporting the formation of zirconium carbide, a rind-like microstructure feature that was proposed to mitigate the chemical interaction. Furthermore, the plasmon peak map was also found to indicate an energy shift associated with the formation of phases/compounds. K-means clustering method was used on the processed electron energy loss (EEL) spectrum to automatically reveal different phases. The resulting clustered maps from K-means clustering align well with elemental maps confirming certain phases, especially Fe-Ce and Zr-C, in the FCCI region.

EELS↗

Combined Gamma Ray/neutron Spectroscopy for Mapping Lunar Resources

Some elements in the Moon can be resources, such as hydrogen and oxygen. Other elements, like Ti or the minerals in which they occur, such as ilmenite, could be used in processing lunar materials. Certain elements can also be used as tracers for other elements or lunar processes, such as hydrogen for mature regoliths with other solar-wind-implanted elements like helium, carbon, and nitrogen. A complete knowledge of the elemental composition of a lunar region is desirable both in identifying lunar resources and in lunar geochemical studies, which also helps in identifying and using lunar resources. The use of gamma ray and neutron spectroscopy together to determine abundances of many elements in the top few tens of centimeters of the lunar surface is discussed. To date, very few discussions of elemental mapping of planetary surfaces considered measurements of both gamma rays and the full range of neutron energies. The theories for gamma ray and neutron spectroscopy of the Moon and calculations of leakage fluxes are presented here with emphasis on why combined gamma ray/neutron spectroscopy is much more powerful than measuring either radiation alone.

Reedy, R. C.↗

First 14-Layer Twinned Hexagonal Perovskite Ba 14 Mn 1.75 Ta 10.5 O 42 : Atomic-Scale Imaging of Cation Ordering

Formation of hexagonal perovskite with mixed cubic and hexagonal stacking of AO 3 layers becomes more and more difficult when the number of layers in the stacking repeating unit increases. So far, the highest number of layers reported for twinned hexagonal perovskite is 12, with alternative 5 consecutive cubic layers and one hexagonal layer in the (ccccch) 2 sequence. Here, we present the unexpected formation of a 14-layer twinned hexagonal perovskite with a stacking sequence (cccccch) 2 for the BaO 3 layers on the Ba 14 Mn 1.75 Ta 10.5 O 42 (Ba 8 MnTa 6 O 24 ) composition, the first example of twinned hexagonal perovskite with a periodicity exceeding 12-layers. The B-cation and vacancy distributions are characterized by multiple efficient and complementary techniques including neutron and synchrotron powder diffraction, scanning transmission electron microscopy-high angle annular dark field (STEM-HAADF) imaging, and electron energy loss spectroscopy (EELS) and X-ray energy dispersive spectroscopy (EDS) elemental mapping. Atomic-resolution STEM-HAADF imaging and EELS/EDS elemental mapping enables direct observation of high-spin d 5 Mn 2+ cation ordering in the d 0 Ta 5+ host, thus demonstrating the great potential of this technique for probing cation ordering and performing structure determination. Moreover, atomic mapping allows for the observation of local defect structure variants, which can be a powerful tool for future new material design. The large high-spin Mn 2+ cation and Ta-vacancy pair formation in face-sharing octahedral sites play key roles on both the stabilization of this 14-layer twinned hexagonal perovskite structure and the Mn 2+ ordering in the central corner-sharing octahedral (CSO) positions within the five-consecutive CSO layers. Here, compared with the 8-layer twinned Ba 8 ZnTa 6 O 24 material, the low quality factor in microwave frequency and enhanced ultraviolet and visible light absorption of Ba 14 Mn 1.75 Ta 10.5 O 42 as well as the photocatalytic activity on water splitting are discussed in terms of the presence of high-spin Mn 2+ cations in the structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High Precision and Spatial Resolution Chemical Interrogation of Planetary Materials Using fs-LA/LIBS in Tandem With Multi-Collector ICP-MS

Combining femtosecond laser ablation (fs-LA) with laser-induced breakdown spectroscopy (LIBS), together with multi-collector inductively coupled plasma mass spectrometry (MC-ICPMS), can provide remarkable insights into the composition, structure, and therefore geologic history of planetary materials and their terrestrial analogs. Using the Applied Spectra iX-fs-Tandem LA-LIBS Instrument and the Nu SP1700 MC-ICP-MS housed within the Center for Isotope Cosmochemistry and Geochronology at NASA Johnson Space Center, we present preliminary tandem fs-LA-(MC)-ICP-MS/LIBS measurements of planetary analog materials. The synergistic integration of fs-LA-LIBS offers high spatial resolution elemental mapping, enabling the identification of microscale variations within samples. Simultaneously, the MC-ICP-MS can deliver precise isotopic analyses, and integrating the two datasets yields a wealth of geochemical information for a given sample. LA-based chemical mapping experiment designs are contingent on the information sought (i.e., quantitative, or semi-quantitative) and the preferred or available volume of material removed for the analysis. For example, occasionally, there are significant limitations in the depth of ablation due to the sample value, the amount of material available, or simply the need to coordinate with other in-situ techniques. In these limited sample scenarios, the “depth-controlled” chemical maps allow for precise post-mapping ion-polishing of the sample, while the isotopic and elemental maps can be used for targeting future analyses (e.g., conventional LA analyses, SIMS analyses, and micro milling for solution ICP-MS/TIMS). The emerging methodology will establish a powerful tool for investigation of astromaterials and materials returned by future planetary sample science missions.

Jacob B Setera↗

Sky and Elemental Planetary Mapping Via Gamma Ray Emissions

Low-energy gamma ray emissions ((is) approximately 30keV to (is) approximately 30MeV) are significant to astrophysics because many interesting objects emit their primary energy in this regime. As such, there has been increasing demand for a complete map of the gamma ray sky, but many experiments to do so have encountered obstacles. Using an innovative method of applying the Radon Transform to data from BATSE (the Burst And Transient Source Experiment) on NASA's CGRO (Compton Gamma-Ray Observatory) mission, we have circumvented many of these issues and successfully localized many known sources to 0.5 - 1 deg accuracy. Our method, which is based on a simple 2-dimensional planar back-projection approximation of the inverse Radon transform (familiar from medical CAT-scan technology), can thus be used to image the entire sky and locate new gamma ray sources, specifically in energy bands between 200keV and 2MeV which have not been well surveyed to date. Samples of these results will be presented. This same technique can also be applied to elemental planetary surface mapping via gamma ray spectroscopy. Due to our method's simplicity and power, it could potentially improve a current map's resolution by a significant factor.

BATSE (the Burst and Transient Source Experiment)↗

NanoSIMS opens a New Window for Deciphering Organic Matter in Terrestrial and Extraterrestrial Samples

Recognition of the earliest morphological or chemical evidence of terrestrial life has proved to be challenging, as organic matter in ancient rocks is commonly fragmentary and difficult to distinguish from abiotically-produced materials (Schopf, 1993; Van Zuilen et al., 2002; Altermann & Kazmierczak, 2003; Cady et al., 2003; Brasier et al., 2002, 2004, 2005; Hofmann, 2004; Skrzypczak et al., 2004, 2005). Yet, the ability to identify remnants of earliest life is critical to our understanding of the timing of life's origin on earth, the nature of earliest terrestrial life, and recognition of potential remnants of microbial life that might occur in extraterrestrial materials. The search for earliest life on Earth now extends to early Archean organic remains; these tend to be very poorly preserved and considerably more difficult to interpret than the delicately permineralized microfossils known from many Proterozoic deposits. Thus, recent efforts have been directed toward finding biosignatures that can help distinguish fragmentary remnants of ancient microbes from either pseudofossils or abiotic organic materials that may have formed hydrothermally or in extraterrestrial processes (House et al., 2000; Boyce et al., 2001; Kudryavtsev et al., 2001; Schopf, 2002; Schopf et al., 2002, 2005a,b; Cady et al., 2003; Garc a-Ruiz et al., 2003; Hofmann, 2004; Brasier et al., 2005; Rushdi and Simoneit, 2005; Skrzypczak et al., 2005). An exciting area of biosignature research involves the developing technology of NanoSIMS. NanoSIMS is secondary ion mass spectrometry (SIMS) for ultrafine feature, elemental and isotopic analysis. Its resolution approaches 0.05 micrometers for element mapping, which is 10-50 times finer than that attainable with conventional SIMS or electron microprobes. Consequently, NanoSIMS has the potential to reveal previously unknown, chemical and structural characteristics of organic matter preserved in geologic materials. Robert et al. (2005) were the first to combine NanoSIMS element maps with optical microscopic imagery in an effort to develop a new method for assessing biogenicity. They showed that the ability to simultaneously map the distribution of organic elements [such as carbon (C), nitrogen (N), and sulfur (S)] and compare those element distributions with optically recognizable, cellularly preserved fossils could provide significant new insights into the origin of organic materials in ancient sediments. This chapter details a recent NanoSIMS study which was designed to acquire new data relevant to establishing critical biosignatures (Oehler et al., 2006a-c). In this study, NanoSIMS was used to characterize element distributions of spheroidal and filamentous microfossils and associated organic laminae in chert from the approx. 0.85 billion year old (Ga) Bitter Springs Formation of Australia. Previous work established preservation of a diverse microbiota in the Bitter Springs Formation (Schopf, 1968; Schopf and Blacic, 1971), and there is no dispute within the scientific community regarding the biogenicity of any of the Bitter Springs structures evaluated in this new study. Thus, the NanoSIMS results described below provide new insight into - and can be used as a guide for assessing - the origin of less well understood organic materials that may occur in early Archean samples and in meteorites or other extraterrestrial samples.

Oehler, Dorothy ZS.↗

Reduced electron exposure for energy-dispersive spectroscopy using dynamic sampling

Analytical electron microscopy and spectroscopy of biological specimens, polymers, and other beam sensitive materials has been a challenging area due to irradiation damage. There is a pressing need to develop novel imaging and spectroscopic imaging methods that will minimize such sample damage as well as reduce the data acquisition time. The latter is useful for high-throughput analysis of materials structure and chemistry. Here, in this work, we present a novel machine learning based method for dynamic sparse sampling of EDS data using a scanning electron microscope. Our method, based on the supervised learning approach for dynamic sampling algorithm and neural networks based classification of EDS data, allows a dramatic reduction in the total sampling of up to 90%, while maintaining the fidelity of the reconstructed elemental maps and spectroscopic data. In conclusion, we believe this approach will enable imaging and elemental mapping of materials that would otherwise be inaccessible to these analysis techniques.

36 MATERIALS SCIENCE↗

ROI-Finder : machine learning to guide region-of-interest scanning for X-ray fluorescence microscopy

The microscopy research at the Bionanoprobe (currently at beamline 9-ID and later 2-ID after APS-U) of Argonne National Laboratory focuses on applying synchrotron X-ray fluorescence (XRF) techniques to obtain trace elemental mappings of cryogenic biological samples to gain insights about their role in critical biological activities. The elemental mappings and the morphological aspects of the biological samples, in this instance, the bacterium Escherichia coli ( E. Coli ), also serve as label-free biological fingerprints to identify E. coli cells that have been treated differently. The key limitations of achieving good identification performance are the extraction of cells from raw XRF measurements via binary conversion, definition of features, noise floor and proportion of cells treated differently in the measurement. Automating cell extraction from raw XRF measurements across different types of chemical treatment and the implementation of machine-learning models to distinguish cells from the background and their differing treatments are described. Principal components are calculated from domain knowledge specific features and clustered to distinguish healthy and poisoned cells from the background without manual annotation. The cells are ranked via fuzzy clustering to recommend regions of interest for automated experimentation. The effects of dwell time and the amount of data required on the usability of the software are also discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Spatially Resolved Elemental Analysis, Spectroscopy and Diffraction at the GSECARS Sector at the Advanced Photon Source

X‐ray microprobes (XRM) coupled with high‐brightness synchrotron X‐ray facilities are powerful tools for environmental biogeochemistry research. One such instrument, the XRM at the Geo Soil Enviro Center for Advanced Radiation Sources Sector 13 at the Advanced Photon Source (APS; Argonne National Laboratory, Lemont, IL) was recently improved as part of a canted undulator geometry upgrade of the insertion device port, effectively doubling the available undulator beam time and extending the operating energy of the branch supporting the XRM down to the sulfur K edge (2.3 keV). Capabilities include rapid, high‐resolution, elemental imaging including fluorescence microtomography, microscale X‐ray absorption fine structure spectroscopy including sulfur K edge capability, and microscale X‐ray diffraction. These capabilities are advantageous for (i) two‐dimensional elemental mapping of relatively large samples at high resolution, with the dwell times typically limited only by the count times needed to obtain usable counting statistics for low concentration elements, (ii) three‐dimensional imaging of internal elemental distributions in fragile hydrated specimens, such as biological tissues, avoiding the need for physical slicing, (iii) spatially resolved speciation determinations of contaminants in environmental materials, and (iv) identification of contaminant host phases. In this paper, we describe the XRM instrumentation, techniques, applications demonstrating these capabilities, and prospects for further improvements associated with the proposed upgrade of the APS. Core Ideas X‐ray microprobes are powerful tools for environmental biogeochemistry. Upgraded GSECARS XRM operates down to the sulfur K edge. Capabilities: spatially resolved elemental analysis, spectroscopy, and diffraction. Advanced Photon Source upgrade will further advance XRM capabilities.

Sutton, Stephen R.↗