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At least 37 records · Page 2

Organic contamination detection for isotopic analysis of water by laser spectroscopy

Hydrogen and oxygen stable isotope ratios (δ 2 H, δ 17 O, and δ 18 O values) are commonly used tracers of water. These ratios can be measured by isotope ratio infrared spectroscopy (IRIS). However, IRIS approaches are prone to errors induced by organic compounds present in plant, soil, and natural water samples. A novel approach using 17 O-excess values has shown promise for flagging spectrally contaminated plant samples during IRIS analysis. A systematic assessment of this flagging system is needed to prove it useful. Errors induced by methanol and ethanol water mixtures on measured IRIS and isotope ratio mass spectrometry (IRMS) results were evaluated. For IRIS analyses both liquid- and vapour-mode (via direct vapour equilibration) methods are used. The δ 2 H, δ 17 O, and δ 18 O values were measured and compared with known reference values to determine the errors induced by methanol and ethanol contamination. In addition, the 17 O-excess contamination detection approach was tested. This is a post-processing detection tool for both liquid and vapour IRIS triple-isotope analyses, utilizing calculated 17 O-excess values to flag contaminated samples. Organic contamination induced significant errors in IRIS results, not seen in IRMS results. Methanol caused larger errors than ethanol. Results from vapour-IRIS analyses had larger errors than those from liquid-IRIS analyses. The 17 O-excess approach identified methanol driven error in liquid- and vapour-mode IRIS samples at levels where isotope results became unacceptably erroneous. For ethanol contaminated samples, a mix of erroneous and correct flagging occurred with the 17 O-excess method. Here our results indicate that methanol is the more problematic contaminant for data corruption. The 17 O-excess method was therefore useful for data quality control. Organic contamination caused significant errors in IRIS stable isotope results. These errors were larger during vapour analyses than during liquid IRIS analyses, and larger for methanol than ethanol contamination. The 17 O-excess method is highly sensitive for detecting narrowband (methanol) contamination error in vapour and liquid analysis modes in IRIS.

60 APPLIED LIFE SCIENCES↗

Multi-Gas Sensors for Enhanced Reliability of SOFC Operation

GE Research, in partnership with SUNY Polytechnic Institute (SUNY Poly), designed, built, and tested gas sensors for in situ monitoring of H 2 and CO anode tail gases produced with on-site steam reforming in solid oxide fuel cell (SOFC) systems. The knowledge of the H 2 /CO ratio of these anode tail gases should allow accurate determination and control of the efficiency of the reforming process in the SOFC system and should deliver a lower operating cost for SOFC customers. The project objectives were to achieve multi-gas monitoring capability with a single multivariable sensor, and to sustain this performance in the presence of gaseous interferences and a potential poison for the sensor. The duration of the project was 24 months with the project structure that included three technical tasks such as (1) development of design rules of photonic nanostructures for H 2 and CO gas detection, (2) laboratory validation of photonic nanostructures for selective H 2 and CO gas detection, and (3) validation of photonic nanostructures for initial stability and poison-resistance against H 2 S. To build multivariable sensors for selective H 2 and CO gas detection in the presence of interferences, we expanded our earlier knowledge of multi-gas sensors into new fabrication and functionalization methodologies as well as into new methodologies for the spectral data analysis of multi-gas responses. We have advanced our design rules of the three-dimensional (3D) photonic nanostructures that allowed detection of H 2 and CO at high temperatures as individual gases and as their mixtures and rejection of interferences such as CO 2 , H 2 O, CH 4 , and other hydrocarbons for SOFC applications. Our advanced design rules should be attractive for building the new generation of cost-effective industrial sensors. Stability and poison resistance of our 3D photonic nanostructures was tested in the laboratory conditions. While initially we utilized conventional machine learning data analysis tools, we have found that they were unable to correct for the sensor drift. Thus, we have implemented new methods of machine learning for the analysis of our spectral data. These learnings pave the way to move the future studies into advanced testing of effects of interferences, aging and field tests. In future, our work will continue to advance our sensing designs to operate in conditions with known and unknown interferences by implementing nanostructures with enhanced spectral diversity of responses to gaseous species of interest and interferences. Our systematic reduction of technical risks in this completed project and in future studies will ensure transition of this sensing technology to commercialization.

03 NATURAL GAS↗

Quantitative analysis of Cu XANES spectra using linear combination fitting of binary mixtures simulated by FEFF9

We report x-ray absorption near edge structure (XANES) is a powerful tool to probe the fingerprint of local structures, and when coupled with X-ray microscopy, the small spot size enables one to probe very specific regions of interest in a device or material, e.g. interfaces/bulk, different grains, good/bad electrical areas. In this work, we investigate the use of linear combination fitting (LCF) of XANES spectra for the particular case of Cu doping in CdTe. We show that the experimental data seem to be accurately represented by standards of Cu 2 Te and its substoichiometric counterpart, Cu 1.43 Te. We use Cu in CdTe as a case study to evaluate the accuracy of linear combination fitting using simulated standards, given that experimental standards for certain phases (e.g. Cu 1.43 Te) or defect structures (e.g. vacancies) cannot be readily obtained. We discuss how spectral features of the FEFF9-simulated standards, fitting ranges, and noise levels all dictate the accuracy of this type of analysis. We show that the greater the spectral difference between the two standards, the better the LCF is able to differentiate between the two structures and to tolerate experimental noise. Finally, we estimate the error of the fitted weights for different spectral features and noise levels and propose a framework to study local structures semi-quantitatively by using binary mixtures of FEFF9-simulated standards.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Probing the origin of the two-component structure of broad-line region by reverberation mapping of an extremely variable quasar

ABSTRACT The physical origins of quasar components, such as the broad-line region (BLR) and dust torus, remain under debate. To gain insights into them, we focused on changing-state quasars (CSQs) which provide a unique perspective through structural changes associated with accretion disc state transitions. We targeted SDSS J125809.31+351943.0, an extremely variable CSQ, to study its central core structure and kinematics. We conducted reverberation mapping with optical spectroscopy to explore the structure of the BLR and estimate the black hole mass. The results from Hβ reverberation mapping indicated a black hole mass of $10^{9.64^{+0.11}_{-0.20}}\rm {M_\odot }$. Additionally, we analysed variations in the optical to X-ray spectral indices, αox, before and after the state transition, to investigate the accretion disc. These variations in αox and the Eddington ratio (from 0.4 per cent to 2.4 per cent) exhibitied behaviour similar to state transitions observed in X-ray binary systems. Spectral analysis of Hβ revealed a predominantly double-peaked profile during dim periods, transitioning to include a single-peaked component as the quasar brightened, suggesting that Hβ contains a mixture of two components. Each of these components has its distinct characteristics: the first is a double-peaked profile that remains stable despite changes in the accretion rate, while the second is a variable single-peaked profile. Using time-lags from reverberation mapping, we estimated the spatial relationships between these BLR components, the accretion disc, and the dust torus. Our results suggest that the BLR consists of two distinct components, each differing in location and origin.

Nagoshi, Shumpei (ORCID:0000000326504322)↗

Comparing Top-Down Proteoform Identification: Deconvolution, PrSM Overlap, and PTM Detection

Generating top-down tandem mass spectra (MS/MS) for complex mixtures of proteoforms has become possible through improvements in fractionation, on-line separation, dissociation, and mass analysis. The algorithms to match tandem mass spectra to sequences have undergone a parallel evolution, with both spectral alignment and peak matching being paired with diverse methods for scoring proteoform-spectral matches (PrSMs). This study assesses state-of-the-art algorithms for top-down identification through three distinct challenges. The first is identifying a large yield of PrSMs while controlling false discovery rate (FDR) in identifying thousands of proteoforms from complex cell lysates via four software workflows: ProSight Proteome Discoverer, TopPIC, Informed Proteomics, and pTop. The second is the deconvolution of data from both Thermo Orbitrap-class and Bruker maXis Q-TOF instruments to produce consistent precursor charge and mass determinations while generating fragment mass lists to optimize identification. The third attempts to detect diverse post-translational modifications (PTMs) in proteoforms from cow milk and human ovarian tissue. The data demonstrate that existing software suites produce admirable sensitivity, in some cases identifying a third of collected tandem mass spectra with FDR controlled below 2%; the overlap in these PrSMs, however, illustrates real value in searching data with multiple search engines. Differences among identification workflows seem to result from each search algorithm incorporating its own deconvolution algorithm. By transmitting deconvolution data from multiple deconvolution routes (Thermo Xtract, Bruker Auto MSn, Mascot Distiller, TopFD, and FLASHDeconv) to the downstream TopPIC search algorithm, we were able to detect common causes of deconvolution disagreement. The detection of PTMs was very inconsistent among search algorithms, with some workflows suggesting as little as 1% of PrSMs from cow’s milk were singly-phosphorylated while other workflows found that 18% of PrSMs were singly-phosphorylated. Taken together, these results make a strong argument for top-down researchers to adopt a standard practice of analyzing each MS/MS experiment with at least two different search engines.

59 BASIC BIOLOGICAL SCIENCES↗

Effective methylation of phosphonic acids related to chemical warfare agents mediated by trimethyloxonium tetrafluoroborate for their qualitative detection and identification by gas chromatography-mass spectrometry

The effective methylation of phosphonic acids related to chemical warfare agents (CWAs) employing trimethyloxonium tetrafluoroborate (TMO·BF 4 ) for their qualitative detection and identification by gas chromatography-mass spectrometry (GC-MS) is presented. The methylation occurs in rapid fashion (1 h) and can be conveniently carried out at ambient temperature, thus providing a safer alternative to the universally employed diazomethane-based methylation protocols. Optimization of the methylation parameters led us to conclude that methylene chloride was the ideal solvent to carry out the derivatization, and that even though methylated products can be observed surfacing after only 1 h, additional time was not found to be detrimental but beneficial to the process particularly when dealing with analytes at low concentrations (~10 μg mL -1 ). Due to its insolubility in methylene chloride, TMO·BF 4 conveniently settles to the bottom during the reaction and does not produce additional interfering by-products that may further complicate the GC-MS analysis. We demonstrated the method to successfully methylate a variety of Schedule 2 phosphonic acids, including their half esters, resulting in derivatives that were readily detected and identified using the instrument's spectral library. Most importantly, the method was shown to simultaneously methylate a mixture of the organophosphorus-based nerve agent hydrolysis products: pinacolyl methylphosphonate (PMPA), cyclohexyl methylphosphonate (CyMPA) and ethyl methylphosphonate (EMPA) (at a 10 μg mL - 1 concentration each) in a fatty acid ester-rich organic matrix (OPCW-PT-O 3 ) featured in the 38th Organisation for the Prohibition of Chemical Weapons (OPCW) Proficiency Test. Additionally, the protocol was found to effectively methylate N,N-diethylamino ethanesulfonic acid and N,N-diisopropylamino ethanesulfonic acid that are products arising from the oxidative degradation of the V-series agents VR and VX respectively. This work described herein represents the first report on the use of TMO·BF 4 as a viable, stable and safe agent for the methylation of phosphonic acids and their half esters and within the context of an OPCW Proficiency Test sample analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evaluation of B&W UO2/ThO2 VIII experimental core: criticality and thermal disadvantage factor analysis

In the framework of the OECD/NEA International Reactor Physics Experiment (IRPHE) Project, an evaluation of core VIII of the Babcock & Wilcox (B&W) Spectral Shift Control Reactor (SSCR) critical experiment program was performed. The SSCR concept, moderated and cooled by a variable mixture of heavy and light water, envisaged changing of the thermal neutron spectrum during the operation to encourage breeding and to sustain the core criticality. Core VIII contained 2188 fuel rods with 93% enriched UO2-ThO2 fuel in a moderator mixture of heavy and light water. The criticality experiment and measurements of the thermal disadvantage factor were evaluated.

Criticality↗

Interpretable machine learning models classify minerals via spectroscopy

Developing methods to identify mineral species confidently and rapidly from Raman spectral analysis is critical to numerous fields. Traditionally, analysis relies on pattern matching the Raman spectrum of an unknown dataset with a supporting library of well-characterized spectral data, which may prove difficult for environmental samples that are poorly crystalline or phase mixtures. Here, we developed interpretable machine learning models that can classify uranium minerals by secondary oxyanion chemistry and other physicochemical properties based solely on Raman spectra. This new ML method produces a mineral profile of physical and chemical properties for an unknown sample and can rapidly classify or identify unknown minerals from Raman data, without the need for an exact pattern match in a spectral library. Training models are validated by 1. Strong correlation of high confidence model regions with published spectroscopic assignments and 2. Correct classification of a mineral not present in training data. Training data are from the Compendium of Uranium Raman and Infrared Experimental Spectra and available crystallographic information files within the open-source Smart Spectral Matching scientific framework. Physically meaningful classifier models can rapidly identify key structural and chemical information about unknown uranium minerals and the overall methodology is broadly applicable for mineral phases.

Machine learning↗

Analysis of Te and TeO 2 on CdZnTe Nuclear Detectors Treated with Hydrogen Bromide and Ammonium-Based Solutions

Surface defects caused during cutting and polishing in the fabrication of cadmium zinc telluride (CdZnTe) nuclear detectors limit their spectral performance. Chemical treatments are often used to remove surface damages and defects. In this paper, we present the analysis of Te and TeO 2 species on the surfaces of CdZnTe nuclear detectors treated with hydrogen bromide and ammonium-based solutions. The CdZnTe wafers were chemo-mechanically polished in a mixture of hydrogen bromide in hydrogen peroxide and ethylene glycol, followed by a chemical passivation in a mixture of ammonium fluoride and hydrogen peroxide solution. X-ray photoelectron spectroscopy showed significant conversion of Te to TeO 2 , thus producing a more chemically stable surface. The resistivity of the CdZnTe samples is in the order of 1010 ohms-cm. The current for a given applied voltage increased following the passivation and decreased after a 3-hour period. Results from spectral response measurements showed that the 59.5-keV gamma-peak of Am-241 was stable under the same channel for the surface treatment processes.

36 MATERIALS SCIENCE↗

Evaluation of B and W UO{sub 2}/ThO{sub 2} VIII Experimental Core: Criticality and Thermal Disadvantage Factor Analysis

In the framework of the OECD/NEA International Reactor Physics Experiment (IRPHE) Project, an evaluation of core VIII of the Babcock and Wilcox (B and W) Spectral Shift Control Reactor (SSCR), critical experiment program was performed. The SSCR concept, moderated and cooled by a variable mixture of heavy and light water, envisaged changing of the thermal neutron spectrum during the operation to encourage breeding and to sustain the core criticality. Core VIII contained 2188 fuel rods with 93% enriched UO{sub 2}-ThO{sub 2} fuel in a moderator mixture of heavy and light water. The criticality experiment and measurements of the thermal disadvantage factor were evaluated. Benchmark criticality results using different cross-section libraries are reported. ENDF/B-VI.6 calculation was run using the S(α, β) model based on ENDF/B-VI.3 data while ENDF/B-VII.0 and ENDF/BVII.1 used an S(α, β) model based on ENDF/B-VII.0 data. JEFF calculations were run using the S(α, β) model based on JEFF 3.1.1 data except for the aluminum isotope, for which the S(α, β) model was missing. The maximum absolute deviation from the benchmark model was obtained using the JEFF-3.1.1 cross sections while closer results were obtained using ENDF/ B-VII.0 and ENDF/B-VII.1. Only ENDF/B-VII.1 and ENDF/B-VII.0 results are inside the 3σ uncertainty band (+2.8σ and 2.4σ, respectively), having deviations on the order of 300 pcm. The maximum deviation is -827 pcm (-6.1σ), using JEFF.3.1.1. Sample calculations of the TDF benchmark were also performed, studying the effects of the main nuclear data libraries. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Application of Genetic Algorithm (GA) Assisted Partial Least Square (PLS) Analysis on Trilinear and Non-trilinear Fluorescence Data Sets to Quantify the Fluorophores in Multifluorophoric Mixtures: Improving Quantification Accuracy of Fluorimetric Estimations of Dilute Aqueous Mixtures

Excitation-emission matrix fluorescence (EEMF) and total synchronous fluorescence spectroscopy (TSFS) are the 2 fluorescence techniques that are commonly used for the analysis of multifluorophoric mixtures. These 2 fluorescence techniques are conceptually different and provide certain advantages over each other. The manual analysis of such highly correlated large volume of EEMF and TSFS towards developing a calibration model is difficult. Partial least square (PLS) analysis can analyze the large volume of EEMF and TSFS data sets by finding important factors that maximize the correlation between the spectral and concentration information for each fluorophore. However, often the application of PLS analysis on entire data sets does not provide a robust calibration model and requires application of suitable pre-processing step. The present work evaluates the application of genetic algorithm (GA) analysis prior to PLS analysis on EEMF and TSFS data sets towards improving the precision and accuracy of the calibration model. The GA algorithm essentially combines the advantages provided by stochastic methods with those provided by deterministic approaches and can find the set of EEMF and TSFS variables that perfectly correlate well with the concentration of each of the fluorophores present in the multifluorophoric mixtures. The utility of the GA assisted PLS analysis is successfully validated using (i) EEMF data sets acquired for dilute aqueous mixture of four biomolecules and (ii) TSFS data sets acquired for dilute aqueous mixtures of four carcinogenic polycyclic aromatic hydrocarbons (PAHs) mixtures. In the present work, it is shown that by using the GA it is possible to significantly improve the accuracy and precision of the PLS calibration model developed for both EEMF and TSFS data set. Hence, GA must be considered as a useful pre-processing technique while developing an EEMF and TSFS calibration model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-Field One-Dimensional and Two-Dimensional 27Al Magic-Angle Spinning Nuclear Magnetic Resonance Study of ?-, d-, and ?-Al2O3 Dominated Aluminum Oxides: Toward Understanding the Al Sites in ?-Al2O3

Herein, a detailed analysis was carried out using high-field (19.9 T) 27Al magic-angle spinning (MAS) nuclear magnetic resonance (NMR) on three specially prepared aluminum oxide samples where the ?-, d-, and ?-Al2O3 phases are dominantly expressed through careful control of the synthesis conditions. Specifically, two-dimensional (2D) multiquantum (MQ) MAS 27Al was used to obtain high spectral resolution, which provided a guide for analyzing quantitative 1D 27Al NMR spectra. Six aluminum sites were resolved in the 2D MQ MAS NMR spectra, and seven aluminum sites were required to fit the 1D spectra. A set of octahedral and tetrahedral peaks with well-defined quadrupolar line shapes was observed in the ?-phase dominant sample and was unambiguously assigned to the ?-Al2O3 phase. The distinct line shapes related to the ?-Al2O3 phase provided an opportunity for effectively deconvoluting the more complex spectrum obtained from the d-Al2O3 dominant sample, allowing the peaks/quadrupolar parameters related to the d-Al2O3 phase to be extracted. The results show that the d-Al2O3 phase contains three distinct AlO sites and three distinct AlT sites. This detailed Al site structural information offers a powerful way of analyzing the most complex ?-Al2O3 spectrum. It is found that the ?-Al2O3 phase consists of Al sites with local structures similar to those found in the d-Al2O3 and ?-Al2O3 phases albeit with less ordering. Spin–lattice relaxation time measurement further confirms the disordering of the lattice. Collectively, this study uniquely assigns 27Al features in transition aluminas, offering a simplified method to quantify complex mixtures of aluminum sites in transition alumina samples.

Xu, Suochang↗

A Piecewise Local Partial Least Squares (PLS) Method for the Quantitative Analysis of Plutonium Nitrate Solutions

We have developed a piecewise local (PL) partial least squares (PLS) analysis method for total plutonium measurements by absorption spectroscopy in nitric acid-based nuclear material processing streams. Instead of using a single PLS model that covers all expected solution conditions, the method selects one of several local models based on an assessment of solution absorbance, acidity, and Pu oxidation state distribution. The local models match the global model for accuracy against the calibration set, but were observed in several instances to be more robust to variations associated with measurements in the process. The improvements are attributed to the relative parsimony of the local models. Not all of the sources of spectral variation are uniformly present at each part of the calibration range. Thus, the global model is locally overfitting and susceptible to increased variance when presented with new samples. A second set of models quantifies the relative concentrations of Pu(III), (IV), and (VI). Standards containing a mixture of these species were not at equilibrium due to a disproportionation reaction. Therefore, a separate principal component analysis is used to estimate of the concentrations of the individual oxidation states in these standards in the absence of independent confirmatory analysis. The PL analysis approach is generalizable to other systems where the analysis of chemically complicated systems can be aided by rational division of the overall range of solution conditions into simpler sub-regions.

47 OTHER INSTRUMENTATION↗

Fully coupled Pauli-Fierz systems at zero and positive temperature

These notes provide an introduction to the spectral analysis of Pauli-Fierz systems at zero and positive temperature. More precisely, we study finite dimensional quantum systems linearly coupled to a single reservoir, a massless scalar quantum field. We emphasize structure results valid at arbitrary system-reservoir coupling strength. The notes contain a mixture of known, refined, and new results and each section ends with a discussion of open problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Comprehensive analysis of common polymers using hyphenated TGA-FTIR-GC/MS and Raman spectroscopy towards a database for micro- and nanoplastics identification, characterization, and quantitation

Environmental contamination by micro- and nanoplastics (MNPs) is well documented with potential for their increased accumulation globally. Growing public concern over environmental, ecological, and human exposure to MNPs has led to exponential increase in publications, news articles, and reports. Significant knowledge gap exists in standardized analytical methods for the identification and quantification of MNPs from real world environmental samples. Here, in this study, we report comprehensive datasets utilizing thermogravimetric analyzer (TGA) coupled to a Fourier transformed infrared spectrometer (FTIR) and a gas chromatography/mass spectrometer (GC/MS) with corresponding Raman spectral data for the most common polymers documented to be present in the environment (35 plastics of 12 polymer types), to serve as a base line reference for the identification and quantitation of MNPs. Various parameters for TGA-FTIR-GC/MS data acquisition were optimized. Commercial consumer plastic product compositions were identified using this analytical database. Case studies to showcase the utility of the method for polymer mixtures analysis is included. This dataset would serve towards the development of a collaborative, global, comprehensive, and curated public database for the identification of various MNPs and mixtures.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

X-ray diffraction analysis of LiCu{sub 2}O{sub 2} crystals with additives of silver atoms

Silver-containing LiCu{sub 2}O{sub 2} crystals up to 4 × 8 × 8 mm in size were grown by the crystallization of 80(1-x)CuO · 20{sub x}AgNO{sub 3} · 20Li{sub 2}CO{sub 3} (0 ≤ x ≤ 0.5) mixture melt. According to the X-ray spectral and Rietveld X-ray diffraction data, the maximum amount of silver incorporated in the LiCu{sub 2}O{sub 2} structure is about 4 at % relative to the copper content. It was established that silver atoms occupy statistically crystallographic positions of lithium atoms. The incorporation of silver atoms is accompanied by a noticeable increase in parameter c of the LiCu{sub 2}O{sub 2} rhombic unit cell, a slight increase in parameter a, and a slight decrease in parameter b.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Spectral and lasing characteristics of 1% Ho:YAG ceramics under intracavity pumping

High-transparency 1% Ho:YAG ceramics with the transmission coefficient of 82% in the IR range at the sample thickness of 1 mm are synthesised from a mixture of the Ho:Y{sub 2}O{sub 3} and Al{sub 2}O{sub 3} nanopowders obtained by the laser method. Results of investigations of spectral and lasing characteristics of 1 % Ho:YAG ceramics under intracavity pumping by radiation of a 5% Tm:KLuW disk element are presented. Based on spectral intensity analysis of generation in the 1.8 – 2.1 mm range and on cavity parameters, the estimated lasing slope efficiency for 1% Ho:YAG ceramics is about 40%. (lasers)

36 MATERIALS SCIENCE↗