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Introductory guide to backgrounds in XPS spectra and their impact on determining peak intensities

Photoelectron and Auger peaks are central to most of the important uses of x-ray photoelectron spectroscopy (XPS), and thus, they receive the most attention in many types of analysis. Quantitative chemical analysis using XPS requires the assessment of the intensities of the photoemission peaks of the elements detected. Determination of peak intensities requires separation of the photoelectron peak signals from the background on which the peaks rest. For the determination of peak area intensities, the background is subtracted from overall signal intensity. The spectral background is also critical when peak fitting is used to determine intensities of overlapping peaks, and the model of background used in this process can impact the results. In addition to the impact on quantitative analysis, information about the depth distribution of elements in the near surface region can often be obtained by visual inspection of the background and quantified using appropriate modeling. Here, this introductory guide provides some basic information about backgrounds in the XPS analysis, describes the types of background models that are commonly used, suggests some of their strengths and weaknesses, and provides examples of their use and misuse. Although the fundamental nature of some components of the background signals in XPS is not understood, indicating that none of the models in use are fully correct and the area is subject to active research, appropriate good practices have been established for most routine analysis. The guide describes good practices, identifies errors that frequently appear in the literature, and uses examples to demonstrate the impacts of background selections on determinations of peak intensities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multivariate Quantitative Chemical Analysis

Technique of multivariate quantitative chemical analysis devised for use in determining relative proportions of two components mixed and sprayed together onto object to form thermally insulating foam. Potentially adaptable to other materials, especially in process-monitoring applications in which necessary to know and control critical properties of products via quantitative chemical analyses of products. In addition to chemical composition, also used to determine such physical properties as densities and strengths.

Kinchen, David G.↗

Potential Chemical Impacts of CO2 Leakage on Underground Source of Drinking Water Assessed by Quantitative Risk Analysis

Many geologic carbon storage site options include not only excellent storage reservoirs bounded by effective seal layers, but also Underground Sources of Drinking Water (USDWs). An effective risk assessment and mitigation plan provides maximum protection for USDWs, to respect not only current policy but also to accommodate likely future USDW-specific regulatory protections. The goal of this study is to quantify possible risks to USDWs, specifically risks associated with chemical impacts on USDWs. Reactive transport models involve tremendous computational expense. Therefore, a secondary purpose of this study is to develop, calibrate and test reduced order models specifically for assessing risks of USDW chemical impacts by CO2 leakage from a storage reservoir. In order to achieve these goals, a geochemical model was developed to interpret changes in water chemistry following CO2 intrusion. A response surface methodology (RSM) based on these geochemical simulations was used to quantify associated risks. The case study example for this analysis is the Ogallala aquifer overlying the Farnsworth unit (FWU), an active commercial-scale CO2-enhanced oil recovery field. Specific objectives of this study include: (1) to understand how CO2 leakage is likely to influence geochemical processes in aquifer sediments; (2) to quantify potential risks to the Ogallala groundwater aquifer due to CO2 leakage from the FWU oil reservoir; and (3) to identify water chemistry factors for early detection criteria. Results indicate that the leakage rate would most likely range between 10-14 – 10-10 kg/(m2·year) for typical and likely leakage pathway permeability ranges. Within this range of CO2 leakage rate, groundwater quality is not likely to be significantly impacted. The worst-case scenario yields trace metal concentrations approximately twice as much as the initial value, but these predicted concentrations are still less than one-fifth of regulation-stipulated maximum contamination levels and do not exceed the no-impact thresholds. Finally, the results of this analysis suggest that pH may be an effective geochemical indicator of CO2 leakage.

CO2 leakage, USDWs, Groundwater quality, Risk anal↗

Powder diffraction

Powder diffraction is a non-destructive technique, which is experimentally simple in principle. Because the physics behind diffraction is well understood, an exceptionally large amount of information can be obtained from a single measurement. The positions and relative intensities of the peaks yield a fingerprint that can be used for qualitative phase analysis. Quantitative phase analysis can be obtained by detailed analysis of the intensities. Unit cells can be derived from the peak positions. Crystal structures can be solved using powder diffraction data and refined by the Rietveld method. The peak profiles contain information about crystallite size, strain and nanostructure. Non-idealities in the intensities give information on texture. Abandoning the crystallographic model provides information about local structure, by pair distribution function analysis. For powder diffraction, everything is a sample; the technique is commonly applied to characterize minerals, ceramics, metals and alloys, catalysts, polymers, pharmaceuticals, organic compounds, environmental and forensic samples, among others. The major features of contemporary laboratory powder diffractometers are described. Methods for obtaining suitable powder specimens are summarized. Major applications of qualitative and quantitative phase analysis, structure solution, size/strain/nanostructure analysis using peak profiles, texture analysis and pair distribution function analysis are introduced.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Neurofilament protein defines regional patterns of cortical organization in the macaque monkey visual system: a quantitative immunohistochemical analysis

Visual function in monkeys is subserved at the cortical level by a large number of areas defined by their specific physiological properties and connectivity patterns. For most of these cortical fields, a precise index of their degree of anatomical specialization has not yet been defined, although many regional patterns have been described using Nissl or myelin stains. In the present study, an attempt has been made to elucidate the regional characteristics, and to varying degrees boundaries, of several visual cortical areas in the macaque monkey using an antibody to neurofilament protein (SMI32). This antibody labels a subset of pyramidal neurons with highly specific regional and laminar distribution patterns in the cerebral cortex. Based on the staining patterns and regional quantitative analysis, as many as 28 cortical fields were reliably identified. Each field had a homogeneous distribution of labeled neurons, except area V1, where increases in layer IVB cell and in Meynert cell counts paralleled the increase in the degree of eccentricity in the visual field representation. Within the occipitotemporal pathway, areas V3 and V4 and fields in the inferior temporal cortex were characterized by a distinct population of neurofilament-rich neurons in layers II-IIIa, whereas areas located in the parietal cortex and part of the occipitoparietal pathway had a consistent population of large labeled neurons in layer Va. The mediotemporal areas MT and MST displayed a distinct population of densely labeled neurons in layer VI. Quantitative analysis of the laminar distribution of the labeled neurons demonstrated that the visual cortical areas could be grouped in four hierarchical levels based on the ratio of neuron counts between infragranular and supragranular layers, with the first (areas V1, V2, V3, and V3A) and third (temporal and parietal regions) levels characterized by low ratios and the second (areas MT, MST, and V4) and fourth (frontal regions) levels characterized by high to very high ratios. Such density trends may correspond to differential representation of corticocortically (and corticosubcortically) projecting neurons at several functional steps in the integration of the visual stimuli. In this context, it is possible that neurofilament protein is crucial for the unique capacity of certain subsets of neurons to perform the highly precise mapping functions of the monkey visual system.

Non-NASA Center↗

Quantitative proteome analysis of bovine mammary gland reveals protein dynamic changes involved in peak and late lactation stages

Highlights: • Revealed dynamic protein changes between two lactation stages in bovine mammary by TMT-based proteomics (first time). • Longitudinal design avoided the influence of different genetic backgrounds on the DEP detection. • 179 differentially expressed proteins (DEPs) identified. • Identified novel DEPs: AACS, DHCR7, GSTM3, SFRP1 and SFRP4. • Major pathways: PI3K-Akt, localization, lipid metabolic, amino acid transport immune system and apoptotic signaling. Mammary gland is an important organ for milk synthesis and secretion. It undergoes dramatic physiological changes to adapt the shift from peak to late lactation stage. Protein plays a final very vital role in many life functions, and the protein changes during different lactation stages potentially reflect the biology of lactation and the functions of mammary gland in cows. In current study, we adopted tandem mass tags label-based quantitative analysis technique and to investigate proteome changes occurring in bovine mammary gland from peak to late lactation stages. A total of 3753 proteins from mammary tissues taken at two lactation points from four individual cows by biopsy were quantified, out of which 179 proteins were expressed differentially between two stages. We observed five new DEPs (AACS, DHCR7, GSTM3, SFRP1 and SFRP4) and nine functional well-studies known proteins (PLIN2, LPIN1, PLIN3, GSN, CD74, MMP2, SOD1, SOD3 and GPX3) related to milk performance and mammary morphology. Bioinformatics analyses of the DEPs showed a majority of the up-regulated proteins during late lactation stage were related to apoptosis and immune process, while the downregulated proteins were mainly involved in localization, lipid metabolic and transport process. This suggests that the mammary gland can adapt to different molecular functions according to the biological need of the animal. From the integrated analysis of the differentially expressed proteins with known quantitative trait loci and genome-wide association study data, we identified 95 proteins may potentially affect milking performance. We expect findings in this study could be a valuable resource for future studies investigating the bovine proteome and functional studies.

60 APPLIED LIFE SCIENCES↗

Quantitative multielement analysis using high energy particle bombardment

Charged particles ranging in energy from 0.8 to 4.0 MeV are used to induce resonant nuclear reactions, Coulomb excitation (gamma-rays), and X-ray emission in both thick and thin targets. Quantitative analysis is possible for elements from Li to Pb in complex environmental samples, although the matrix can severely reduce the sensitivity. It is necessary to use a comparator technique for the gamma-rays while for X-rays an internal standard can be used. A USGS standard rock is analyzed for a total of 28 elements. Water samples can be analyzed either by nebulizing the sample doped with Cs or Y a thin Formvar film or by extracting the sample onto ion exchange resin which is pressed into a pellet.

Clark, P. J.↗

Quantitative multielement analysis using high energy particle bombardment

Charged particles ranging in energy from 0.8 to 4.0 MeV are used to induce resonant nuclear reactions, Coulomb excitation (gamma X-rays), and X-ray emission in both thick and thin targets. Quantitative analysis is possible for elements from Li to Pb in complex environmental samples, although the matrix can severely reduce the sensitivity. It is necessary to use a comparator technique for the gamma-rays, while for X-rays an internal standard can be used. A USGS standard rock is analyzed for a total of 28 elements. Water samples can be analyzed either by nebulizing the sample doped with Cs or Y onto a thin formvar film or by extracting the sample (with or without an internal standard) onto ion exchange resin which is pressed into a pellet.

Clark, P. J.↗

Chromatic Image Analysis For Quantitative Thermal Mapping

Chromatic image analysis system (CIAS) developed for use in noncontact measurements of temperatures on aerothermodynamic models in hypersonic wind tunnels. Based on concept of temperature coupled to shift in color spectrum for optical measurement. Video camera images fluorescence emitted by phosphor-coated model at two wavelengths. Temperature map of model then computed from relative brightnesses in video images of model at those wavelengths. Eliminates need for intrusive, time-consuming, contact temperature measurements by gauges, making it possible to map temperatures on complex surfaces in timely manner and at reduced cost.

Buck, Gregory M.↗

Visualization techniques to aid in the analysis of multi-spectral astrophysical data sets

The goal of this project was to support the scientific analysis of multi-spectral astrophysical data by means of scientific visualization. Scientific visualization offers its greatest value if it is not used as a method separate or alternative to other data analysis methods but rather in addition to these methods. Together with quantitative analysis of data, such as offered by statistical analysis, image or signal processing, visualization attempts to explore all information inherent in astrophysical data in the most effective way. Data visualization is one aspect of data analysis. Our taxonomy as developed in Section 2 includes identification and access to existing information, preprocessing and quantitative analysis of data, visual representation and the user interface as major components to the software environment of astrophysical data analysis. In pursuing our goal to provide methods and tools for scientific visualization of multi-spectral astrophysical data, we therefore looked at scientific data analysis as one whole process, adding visualization tools to an already existing environment and integrating the various components that define a scientific data analysis environment. As long as the software development process of each component is separate from all other components, users of data analysis software are constantly interrupted in their scientific work in order to convert from one data format to another, or to move from one storage medium to another, or to switch from one user interface to another. We also took an in-depth look at scientific visualization and its underlying concepts, current visualization systems, their contributions, and their shortcomings. The role of data visualization is to stimulate mental processes different from quantitative data analysis, such as the perception of spatial relationships or the discovery of patterns or anomalies while browsing through large data sets. Visualization often leads to an intuitive understanding of the meaning of data values and their relationships by sacrificing accuracy in interpreting the data values. In order to be accurate in the interpretation, data values need to be measured, computed on, and compared to theoretical or empirical models (quantitative analysis). If visualization software hampers quantitative analysis (which happens with some commercial visualization products), its use is greatly diminished for astrophysical data analysis. The software system STAR (Scientific Toolkit for Astrophysical Research) was developed as a prototype during the course of the project to better understand the pragmatic concerns raised in the project. STAR led to a better understanding on the importance of collaboration between astrophysicists and computer scientists.

Brugel, Edward W.↗

Visualization techniques to aid in the analysis of multispectral astrophysical data sets

The goal of this project was to support the scientific analysis of multi-spectral astrophysical data by means of scientific visualization. Scientific visualization offers its greatest value if it is not used as a method separate or alternative to other data analysis methods but rather in addition to these methods. Together with quantitative analysis of data, such as offered by statistical analysis, image or signal processing, visualization attempts to explore all information inherent in astrophysical data in the most effective way. Data visualization is one aspect of data analysis. Our taxonomy as developed in Section 2 includes identification and access to existing information, preprocessing and quantitative analysis of data, visual representation and the user interface as major components to the software environment of astrophysical data analysis. In pursuing our goal to provide methods and tools for scientific visualization of multi-spectral astrophysical data, we therefore looked at scientific data analysis as one whole process, adding visualization tools to an already existing environment and integrating the various components that define a scientific data analysis environment. As long as the software development process of each component is separate from all other components, users of data analysis software are constantly interrupted in their scientific work in order to convert from one data format to another, or to move from one storage medium to another, or to switch from one user interface to another. We also took an in-depth look at scientific visualization and its underlying concepts, current visualization systems, their contributions and their shortcomings. The role of data visualization is to stimulate mental processes different from quantitative data analysis, such as the perception of spatial relationships or the discovery of patterns or anomalies while browsing through large data sets. Visualization often leads to an intuitive understanding of the meaning of data values and their relationships by sacrificing accuracy in interpreting the data values. In order to be accurate in the interpretation, data values need to be measured, computed on, and compared to theoretical or empirical models (quantitative analysis). If visualization software hampers quantitative analysis (which happens with some commercial visualization products), its use is greatly diminished for astrophysical data analysis. The software system STAR (Scientific Toolkit for Astrophysical Research) was developed as a prototype during the course of the project to better understand the pragmatic concerns raised in the project. STAR led to a better understanding on the importance of collaboration between astrophysicists and computer scientists. Twenty-one examples of the use of visualization for astrophysical data are included with this report. Sixteen publications related to efforts performed during or initiated through work on this project are listed at the end of this report.

Brugel, E. W.↗

Shock compression experiments using the DiPOLE 100-X laser on the high energy density instrument at the European x-ray free electron laser: Quantitative structural analysis of liquid Sn

X-ray free electron laser (XFEL) sources coupled to high-power laser systems offer an avenue to study the structural dynamics of materials at extreme pressures and temperatures. The recent commissioning of the DiPOLE 100-X laser on the high energy density (HED) instrument at the European XFEL represents the state-of-the-art in combining x-ray diffraction with laser compression, allowing for compressed materials to be probed in unprecedented detail. Here, we report quantitative structural measurements of molten Sn compressed to 85(5) GPa and ~3500 K. The capabilities of the HED instrument enable liquid density measurements with an uncertainty of ~1% at conditions which are extremely challenging to reach via static compression methods. We discuss best practices for conducting liquid diffraction dynamic compression experiments and the necessary intensity corrections which allow for accurate quantitative analysis. We also provide a polyimide ablation pressure vs input laser energy for the DiPOLE 100-X drive laser which will serve future users of the HED instrument.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

United States manned spacecraft reliability experience

Attention is given to the reliability controls in manned spacecraft programs, taking into account the project Mercury, the Gemini program, the Apollo program, the Skylab program, and the Apollo-Soyuz test project. Reliability controls used in these programs are related to reliability management, parts and materials control, failure mode and effects analysis, reliability quantitative analysis, problem reporting and corrective action control, test control, limited-life control, and milestone reviews. A summary is presented of the major reliability tasks and innovations being used on the Space Shuttle program. Examples of these innovations include improved management techniques and an early identification of specific certification tests.

Kleinknecht, K. S.↗

Quantitative Schlieren analysis applied to holograms of crystals grown on Spacelab 3

In order to extract additional information about crystals grown in the microgravity environment of Spacelab, a quantitative schlieren analysis technique was developed for use in a Holography Ground System of the Fluid Experiment System. Utilizing the Unidex position controller, it was possible to measure deviation angles produced by refractive index gradients of 0.5 milliradians. Additionally, refractive index gradient maps for any recorded time during the crystal growth were drawn and used to create solute concentration maps for the environment around the crystal. The technique was applied to flight holograms of Cell 204 of the Fluid Experiment System that were recorded during the Spacelab 3 mission on STS 51B. A triglycine sulfate crystal was grown under isothermal conditions in the cell and the data gathered with the quantitative schlieren analysis technique is consistent with a diffusion limited growth process.

Brooks, Howard L.↗

Fusing Quantitative Requirements Analysis with Model-based Systems Engineering

A vision is presented for fusing quantitative requirements analysis with model-based systems engineering. This vision draws upon and combines emergent themes in the engineering milieu. "Requirements engineering" provides means to explicitly represent requirements (both functional and non-functional) as constraints and preferences on acceptable solutions, and emphasizes early-lifecycle review, analysis and verification of design and development plans. "Design by shopping" emphasizes revealing the space of options available from which to choose (without presuming that all selection criteria have previously been elicited), and provides means to make understandable the range of choices and their ramifications. "Model-based engineering" emphasizes the goal of utilizing a formal representation of all aspects of system design, from development through operations, and provides powerful tool suites that support the practical application of these principles. A first step prototype towards this vision is described, embodying the key capabilities. Illustrations, implications, further challenges and opportunities are outlined.

optimization↗

Marine chlorophyll a analysis

Quantitative distribution maps of chlorophyll a and other important environmental parameters of coastal zones are prepared by regression analysis of sea-truth data and data collected by aircraft multispectral scanners.

Johnson, R. W.↗

Quantitative phase analysis of challenging samples using neutron powder diffraction. Sample #4 from the CPD QPA round robin revisited

Here, quantitative phase analysis (QPA) using neutron powder diffraction more often than not involves non-ambient studies where no sample preparation is possible. The larger samples and penetration of neutrons versus X-rays makes neutron diffraction less susceptible to inhomogeneity and large grain sizes, but most well-characterized QPA standard samples do not have these characteristics. Sample #4 from the International Union of Crystallography Commission on Powder Diffraction QPA round robin was one such sample. Data were collected using the POWGEN time-of-flight (TOF) neutron powder diffractometer and analysed together with historical data from the C2 diffractometer at Chalk River. The presence of magnetic reflections from Fe 3 O 4 (magnetite) in the sample was an additional consideration, and given the frequency at which iron-containing and other magnetic compounds are present during in-operando studies their possible impact on the accuracy of QPA is of interest. Additionally, scattering from thermal diffuse scattering in the high- Q region (<0.6 Å) accessible with TOF data could impact QPA results during least-squares because of the extreme peak overlaps present in this region. Refinement of POWGEN data was largely insensitive to the modification of longer d -spacing reflections by magnetic contributions, but the constant-wavelength data were adversely impacted if the magnetic structure was not included. A robust refinement weighting was found to be effective in reducing quantification errors using the constant-wavelength neutron data both where intensities from magnetic reflections were ignored and included. Results from the TOF data were very sensitive to inadequate modelling of the high- Q (low d -spacing) background using simple polynomials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multi-scale Quantitative Risk Analysis of Seabed Minerals: Principles and Application to Seafloor Massive Sulfide Prospects

The potential for mining hydrothermal mineral deposits on the seafloor, such as seafloor massive sulfides, has become technically possible, and some companies (currently not many) are considering their exploration and development. Yet, no present methodology has been designed to quantify the ore potential and assess the risks relative to prospectivity at prospect and regional scales. Multi-scale exploration techniques, similar to those of the play analysis that are used in the oil and gas industry, can help to fulfill this task by identifying the characteristics of geologic environments indicative of ore-forming processes. Such characteristics can represent a combination of, e.g., heat source, pathway, trap and reservoir that all dictate how and where ore components are mobilized from source to deposition. In this study, the understanding of these key elements is developed as a mineral system, which serves as a guide for mapping the risk of the presence or absence of ore-forming processes within the region of interest (the permissive tract). The risk analysis is carried out using geoscience data, and it is paired with quantitative resource estimation analysis to estimate the in-place mineral potential. Resource estimates are simulated stochastically with the help of available data (bathymetric features in this study), conventional grade–tonnage models and Monte Carlo simulation techniques. In this paper, the workflow for a multi-scale quantitative risk analysis, from the definition to the evaluation of a permissive tract and related prospect(s), is described with the help of multi-beam data of a known hydrothermal vent site.

58 GEOSCIENCES↗