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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 OSTI2022

Bioinspired oxidation of benzyl alcohol: The role of environment and nuclearity of the catalyst evaluated by multivariate analysis

Inspired by copper-containing enzymes such as galactose oxidase and catechol oxidase, in which distinct coordination environments and nuclearities lead to specific catalytic activities, we summarize here the catalytic properties of dinuclear and mononuclear copper species towards benzyl alcohol oxidation using a multivariate statistical approach. Here, the new dinuclear [Cu 2 (μ-L 1 )(μ-pz)] 2+ (1) is compared against the mononuclear [CuL 2 Cl] (2), where (L 1 ) - and (L 2 ) - are the respective deprotonated forms of 2,6-bis((bis(pyridin-2-ylmethyl)amino)methyl)-4-methylphenol, and 3-((bis(pyridin-2-ylmethyl)amino)methyl)-2-hydroxy-5-methylbenzaldehyde and (pz) - is a pyrazolato bridge. Copper(II) perchlorate (CP) is used as control. The catalytic oxidation of benzyl alcohol is pursued, aiming to assess the role of the ligand environment and nuclearity. The multivariate statistical approach allows for the search of optimal catalytic conditions, considering variables such as catalyst load, hydrogen peroxide load, and time. Species 1, 2 and CP promoted selective production of benzaldehyde at different yields, with only negligible amounts of benzoic acid. Under normalized conditions, 2 showed superior catalytic activity. This species is 3.5-fold more active than the monometallic control CP, and points out to the need for an efficient ligand framework. Species 2 is 6-fold more active than the dinuclear 1, and indicates the favored nuclearity for the conversion of alcohols into aldehydes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

Optical Spectroscopy and Multivariate Analysis for Biodosimetry and Monitoring of Radiation Injury to the Skin

In the event of an intentional or accidental release of ionizing radiation in a densely populated area, timely assessment and triage of the general population for the radiation exposure is critical. In particular, a significant number of the victims may sustain cutaneous radiation injury, which increases the mortality and worsens the overall prognosis of the victims suffered from combined thermal/mechanical and radiation trauma. Diagnosis of the cutaneous radiation injury is challenging, and established methods largely rely on visual manifestations, presence of the skin contamination, and a high degree of recall by the victim. Availability of a high throughput non-invasive in vivo biodosimetry tool for assessment of the radiation exposure of the skin is of particular importance for the timely diagnosis of the cutaneous injury. In the reported investigation, we have tested the potential of an optical reflectance spectroscopy for the evaluation of the radiation injury to the skin. This is technically attractive because optical spectroscopy relies on well-established and routinely used for various applications instrumentation, one example being pulse oximetry which uses selected wavelengths for the quantification of the blood oxygenation. Our method relies on a broad spectral region ranging from the locally absorbed, shallow-penetrating ultraviolet and visible (250 to 800 nm) to more deeply penetrating near-Infrared (800 – 1600 nm) light for the monitoring of multiple physiological changes in the skin upon irradiation. Chemometrics is a multivariate methodology that allows the information from entire spectral region to be used to generate predictive regression models. In this report we demonstrate that simple spectroscopic method, such as the optical reflectance spectroscopy, in combination with multivariate data analysis, offers the promise of rapid and non-invasive in vivo diagnosis and monitoring of the cutaneous radiation exposure, and is able accurately predict the dose and time of exposure in the rodent model.

Levitskaia, Tatiana G↗
DOE OSTI2016

Multivariate analysis for the estimation of target localization errors in fiducial marker-based radiotherapy

Purpose: To assess the target localization error (TLE) in terms of the distance between the target and the localization point estimated from the surrogates (|TMD|), the average of respiratory motion for the surrogates and the target (|aRM|), and the number of fiducial markers used for estimating the target (n). Methods: This study enrolled 17 lung cancer patients who subsequently underwent four fractions of real-time tumor tracking irradiation. Four or five fiducial markers were implanted around the lung tumor. The three-dimensional (3D) distance between the tumor and markers was at maximum 58.7 mm. One of the markers was used as the target (P{sub t}), and those markers with a 3D |TMD{sub n}| ≤ 58.7 mm at end-exhalation were then selected. The estimated target position (P{sub e}) was calculated from a localization point consisting of one to three markers except P{sub t}. Respiratory motion for P{sub t} and P{sub e} was defined as the root mean square of each displacement, and |aRM| was calculated from the mean value. TLE was defined as the root mean square of each difference between P{sub t} and P{sub e} during the monitoring of each fraction. These procedures were performed repeatedly using the remaining markers. To provide the best guidance on the answer with n and |TMD|, fiducial markers with a 3D |aRM ≥ 10 mm were selected. Finally, a total of 205, 282, and 76 TLEs that fulfilled the 3D |TMD| and 3D |aRM| criteria were obtained for n = 1, 2, and 3, respectively. Multiple regression analysis (MRA) was used to evaluate TLE as a function of |TMD| and |aRM| in each n. Results: |TMD| for n = 1 was larger than that for n = 3. Moreover, |aRM| was almost constant for all n, indicating a similar scale for the marker’s motion near the lung tumor. MRA showed that |aRM| in the left–right direction was the major cause of TLE; however, the contribution made little difference to the 3D TLE because of the small amount of motion in the left–right direction. The TLE calculated from the MRA ({sup MRA}TLE) increased as |TMD| and |aRM| increased and adversely decreased with each increment of n. The median 3D {sup MRA}TLE was 2.0 mm (range, 0.6–4.3 mm) for n = 1, 1.8 mm (range, 0.4–4.0 mm) for n = 2, and 1.6 mm (range, 0.3–3.7 mm) for n = 3. Although statistical significance between n = 1 and n = 3 was observed in all directions, the absolute average difference and the standard deviation of the {sup MRA}TLE between n = 1 and n = 3 were 0.5 and 0.2 mm, respectively. Conclusions: A large |TMD| and |aRM| increased the differences in TLE between each n; however, the difference in 3D {sup MRA}TLEs was, at most, 0.6 mm. Thus, the authors conclude that it is acceptable to continue fiducial marker-based radiotherapy as long as |TMD| is maintained at ≤58.7 mm for a 3D |aRM| ≥ 10 mm.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Multivariate Analysis of MALDI Imaging Mass Spectrometry Data of Mixtures of Single Pollen Grains

Mixtures of pollen grains of three different species (Corylus avellana, Alnus cordata, and Pinus sylvestris) were investigated by matrix-assisted laser desorption/ionization time-of-flight imaging mass spectrometry (MALDI-TOF imaging MS). The amount of pollen grains was reduced stepwise from > 10 to single pollen grains. For sample pretreatment, we modified a previously applied approach, where any additional extraction steps were omitted. Our results show that characteristic pollen MALDI mass spectra can be obtained from a single pollen grain, which is the prerequisite for a reliable pollen classification in practical applications. MALDI imaging of laterally resolved pollen grains provides additional information by reducing the complexity of the MS spectra of mixtures, where frequently peak discrimination is observed. Combined with multivariate statistical analyses, such as principal component analysis (PCA), our approach offers the chance for a fast and reliable identification of individual pollen grains by mass spectrometry. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Multivariate Analysis for Quantification of Plutonium(IV) in Nitric Acid Based on Absorption Spectra

Development of more effective, reliable, and fast methods for monitoring process streams is a growing opportunity for analytical applications. Many fields can benefit from on-line monitoring, including the nuclear fuel cycle where improved methods for monitoring radioactive materials will facilitate maintenance of proper safeguards and ensure safe and efficient processing of materials. On-line process monitoring with a focus on optical spectroscopy can provide a fast, non-destructive method for monitoring chemical species. However, identification and quantification of species can be hindered by the complexity of the solutions if bands overlap or show condition-dependent spectral features. Plutonium (IV) is one example of a species which displays significant spectral variation with changing nitric acid concentration. Single variate analysis (i.e. Beer’s Law) is difficult to apply to the quantification of Pu(IV) unless the nitric acid concentration is known and separate calibration curves have been made for all possible acid strengths. Multivariate, or chemometric, analysis is an approach that allows for the accurate quantification of Pu(IV) without a priori knowledge of nitric acid concentration.

Lines, Amanda M.↗
DOE OSTI2019

Multivariate Analysis Based on Geochemical, Isotopic, and Mineralogical Compositions of Uranium-Rich Samples

The chemical and isotopic (U, Pb, Sr) signatures for a suite (n = 23) of pristine (>80 wt. % UO 2 ) and altered uraninite samples (>70–80 wt. % UO 2 ) from various locations worldwide have been determined for the purpose of identifying potential fingerprints for nuclear forensic analysis. The characterization of the uraninite samples included determination of major, minor and trace element contents, Sr, Pb, and U isotopic compositions, and secondary mineral assemblages. Due to the multivariate approach adopted in this study, principal component analysis (PCA) has been employed to allow the direct comparison of multiple variable types. The PCA results indicate that the geological origin (sandstone, metamorphite, intrusive, granite and unconformity) of pristine uraninite can be readily identified utilizing various combinations of major and/or trace element concentrations with isotopic compositions.

58 GEOSCIENCES↗
DOE OSTI2019

Multivariate analysis of x-ray scattering using a stochastic source

The normalization of scattered intensity by incident flux is a crucial step in analyzing data from stochastic x-ray free electron laser sources and is complicated by non-linearities traditionally attributed to detector saturation. Here we show that such non-linearities can also arise when the sample spectra are non-uniform within the monochromator bandwidth. A method for modeling and removing this non-linearity using multivariate regression with shot-by-shot x-ray photon energy as an independent variable is presented. In conclusion, this approach demonstrates the benefit of event building and will allow for a reconsideration of data which has proven challenging to normalize.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Multivariate analysis: An essential for studying complex glasses

Understanding the impact of individual compositional components on the devitrification of complex multicomponent glasses, for example, 10–50+ oxides, typically requires numerous studies to examine each component's impact. Here we apply exploratory data analysis (EDA) to a heterogeneous data set of silicate glasses to determine the cations’ individual and interacting effects on the crystallization of nepheline (nominally NaAlSiO 4 ). Our data consisted of 795 simulated high-level nuclear waste glasses composed of, on average, 50 oxide components. We determine the interactions in the heterogeneous data that cause deviations from the behavior found in simplified composition studies. Using both univariate and bivariate EDA techniques, we demonstrate the importance of including calculated structural glass parameters on nepheline's devitrification, including field strength, cation-to-anion radius ratio, and single-bond strength. Here, we also show that studies with simplified glass compositions may fall short in generating knowledge directly transferrable to complex glass compositions. The method used in this study has the potential to inform experimental design for simplified compositions (~6+ oxides) that can generate knowledge directly transferrable to complex, multivariable compositions. The observations reported here have broad implications for any study attempting to map the physical properties of a complex glass containing numerous cations.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Differentiation of Microbial Species and Strains in Coculture Biofilms by Multivariate Analysis of Laser Desorption Postionization Mass Spectra

7.87 to 10.5 eV vacuum ultraviolet (VUV) photon energies were used in laser desorption postionization mass spectrometry (LDPI-MS) to analyze biofilms comprised of binary cultures of interacting microorganisms. The effect of photon energy was examined using both tunable synchrotron and laser sources of VUV radiation. Principal components analysis (PCA) was applied to the MS data to differentiate species in Escherichia coli-Saccharomyces cerevisiae coculture biofilms. PCA of LDPI-MS also differentiated individual E. coli strains in a biofilm comprised of two interacting gene deletion strains, even though these strains differed from the wild type K-12 strain by no more than four gene deletions each out of approximately 2000 genes. PCA treatment of 7.87 eV LDPI-MS data separated the E. coli strains into three distinct groups two ?pure? groups and a mixed region. Furthermore, the ?pure? regions of the E. coli cocultures showed greater variance by PCA when analyzed by 7.87 eV photon energies than by 10.5 eV radiation. Comparison of the 7.87 and 10.5 eV data is consistent with the expectation that the lower photon energy selects a subset of low ionization energy analytes while 10.5 eV is more inclusive, detecting a wider range of analytes. These two VUV photon energies therefore give different spreads via PCA and their respective use in LDPI-MS constitute an additional experimental parameter to differentiate strains and species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Water O–H Stretching Raman Signature for Strong Acid Monitoring via Multivariate Analysis

Spectroscopic techniques have been applied extensively for quantification and analysis of solution compositions. In addition to static measurements, these techniques have been implemented in flow systems providing real-time solution information. A distinct need exists for information regarding acid concentration as it affects extraction efficiency and selectivity of many separation processes. Despite of the seeming simplicity of the problem, no practical solution has been offered yet particularly for the large-scale schemes involving toxic streams such as highly radioactive nuclear wastes. Classic potentiometric technique is not amiable for on-line measurements in nuclear fuel reprocessing due to requirements of frequent calibration/maintenance and poor long-term stability in the aggressive chemical and radiation environments. In this work, the potential of using Raman spectroscopic measurements for on-line monitoring of strong acid concentration in the solutions relevant to the dissolved used fuel was investigated. The Raman water signature was monitored and recorded for nitric and hydrochloric acid solution systems of systematically varied chemical composition, ionic strength, and temperature. The generated Raman spectroscopic database was used to develop predictive chemometric models for the quantification of the acid concentration (H+), neodymium concentration (Nd3+), nitrate concentration (NO3-), density, and ionic strength. This approach was validated using a flow solvent extraction system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Multivariable Analysis of Aerodynamic Forces on Slotted Airfoils for Wind Turbine Blades

Improvement of the aerodynamic performance for cambered airfoils with leading-edge slots is investigated in this work. This concept is proven both computationally and experimentally in recent years. Five design variables of interest are slot's length, slot's width or thickness, inlet angle, exit angle, and the vertical position. The objective is to perform design of experiment and optimization studies on these variables and evaluate the behavior of the objective functions, namely lift and lift over drag ratio (LoD), within the appropriate ranges of the independent variables. Simulations are mainly carried out at the Reynolds number of 1.6 × 10 6 and the angles of attack (AoA) of 6 deg for NACA 4412 airfoil. However, some of the analyses are repeated at Reynolds number of 3.2 × 10 6 and AoA of 0 and 8 deg to show the scalability of the results. Results indicate that the proper selection of three of the design variables, i.e., length, inlet angle, and vertical position, can have a significant impact on both lift and LoD, while the other two variables seem less influential. For the combination of the operating conditions and the values of the design variables considered in this investigation, a LoD improvement as large as 11% is observed.

Energy & Fuels↗
DOE OSTI2016

Multivariate analysis techniques

The end products of experimental data analysis are designed to be simple and easy to understand: hypothesis tests and measurements of parameters. But, the experimental data themselves are voluminous and complex. Furthermore, in modern collider experiments, many petabytes of data must be processed in search of rare new processes which occur together with much more copious background processes that are of less interest to the task at hand. The systematic uncertainties on the background may be larger than the expected signal in many cases. The statistical power of an analysis and its sensitivity to systematic uncertainty can therefore usually both be improved by separating signal events from background events with higher efficiency and purity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Multivariate Analysis of Sensor Data NSARD Poster

Poster for the cancelled NSARD meeting. The Federal Program Manager, Angie Waterworth, plans to send posters out to all planned attendees, even though the poster will NO LONGER BE PRESENTED.

97 MATHEMATICS AND COMPUTING↗