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At least 1,459 records · Page 81

Laser-Based Remote Sensing of Explosives by a Differential Absorption and Scattering Method

A multifunctional IR parametric laser system is developed and tested for remote detection and identification of atmospheric gases, including explosive and chemically aggressive substances. Calculations and experimental studies of remote determination of the spectroscopic parameters of the best known explosive substances TNT, RDX, and PETN are carried out. The feasibility of high sensitivity detection (~1 ppm) of these substances with the aid of a multifunctional IR parametric light source by differential absorption and scattering is demonstrated.

42 ENGINEERING↗

A Decision-Making Machine Learning Approach in Hermite Spectral Approximations of Partial Differential Equations

The accuracy and effectiveness of Hermite spectral methods for the numerical discretization of partial differential equations on unbounded domains are strongly affected by the amplitude of the Gaussian weight function employed to describe the approximation space. This is particularly true if the problem is under-resolved, i.e., there are no enough degrees of freedom. The issue becomes even more crucial when the equation under study is time-dependent, forcing in this way the choice of Hermite functions where the corresponding weight depends on time. In order to adapt dynamically the approximation space, it is here proposed an automatic decision-making process that relies on machine learning techniques, such as deep neural networks and support vector machines. The algorithm is numerically tested with success on a simple 1D problem, but the main goal is its exportability in the context of more serious applications. Here we also show at the end an application in the framework of plasma physics.

97 MATHEMATICS AND COMPUTING↗

Boundary Corrections for Kernel Approximation to Differential Operators

The kernel-based approach to operator approximation for partial differential equations has been shown to be unconditionally stable for linear PDEs and numerically exhibit unconditional stability for non-linear PDEs. These methods have the same computational cost as an explicit finite difference scheme but can exhibit order reduction at boundaries. In previous work on periodic domains, order reduction was addressed, yielding high-order accuracy. The issue addressed in this work is the elimination of order reduction of the kernel-based approach for a more general set of boundary conditions. Further, we consider the case of both first and second order operators. To demonstrate the theory, we provide not only the mathematical proofs but also experimental results by applying various boundary conditions to different types of equations. The results agree with the theory, demonstrating a systematic path to high order for kernel-based methods on bounded domains.

97 MATHEMATICS AND COMPUTING↗

An introduction to partial differential equations constrained optimization

Partial differential equation (PDE) constrained optimization is designed to solve control, design, and inverse problems with underlying physics. A distinguishing challenge of this technique is the handling of large numbers of optimization variables in combination with the complexities of discretized PDEs. Over the last several decades, advances in algorithms, numerical simulation, software design, and computer architectures have allowed for the maturation of PDE constrained optimization (PDECO) technologies with subsequent solutions to complicated control, design, and inverse problems. This special journal edition, entitled “PDE-Constrained Optimization”, features eight papers that demonstrate new formulations, solution strategies, and innovative algorithms for a range of applications. In particular, these contributions demonstrate the impactfulness on our engineering and science communities. This paper offers short remarks to provide some perspective and background for PDECO, in addition to summaries of the eight papers.

97 MATHEMATICS AND COMPUTING↗

A genome-wide analysis of the flax (Linum usitatissimum L.) dirigent protein family: from gene identification and evolution to differential regulation

Identification of DIR encoding genes in flax genome. Analysis of phylogeny, gene/protein structures and evolution. Identification of new conserved motifs linked to biochemical functions. Investigation of spatio-temporal gene expression and response to stress. Dirigent proteins (DIRs) were discovered during 8-8' lignan biosynthesis studies, through identification of stereoselective coupling to afford either (+)- or (-)-pinoresinols from E-coniferyl alcohol. DIRs are also involved or potentially involved in terpenoid, allyl/propenyl phenol lignan, pterocarpan and lignin biosynthesis. DIRs have very large multigene families in different vascular plants including flax, with most still of unknown function. DIR studies typically focus on a small subset of genes and identification of biochemical/physiological functions. Herein, a genome-wide analysis and characterization of the predicted flax DIR 44-membered multigene family was performed, this species being a rich natural grain source of 8-8' linked secoisolariciresinol-derived lignan oligomers. All predicted DIR sequences, including their promoters, were analyzed together with their public gene expression datasets. Expression patterns of selected DIRs were examined using qPCR, as well as through clustering analysis of DIR gene expression. These analyses further implicated roles for specific DIRs in (-)-pinoresinol formation in seed-coats, as well as (+)-pinoresinol in vegetative organs and/or specific responses to stress. Phylogeny and gene expression analysis segregated flax DIRs into six distinct clusters with new cluster-specific motifs identified. We propose that these findings can serve as a foundation to further systematically determine functions of DIRs, i.e. other than those already known in lignan biosynthesis in flax and other species. Given the differential expression profiles and inducibility of the flax DIR family, we provisionally propose that some DIR genes of unknown function could be involved in different aspects of secondary cell wall biosynthesis and plant defense.

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Elucidating the Onset of Plasticity in Sliding Contacts Using Differential Computational Orientation Tomography

Abstract Depending on the mechanical and thermal energy introduced to a dry sliding interface, the near-surface regions of the mated bodies may undergo plastic deformation. In this work, we use large-scale molecular dynamics simulations to generate “differential computational orientation tomographs” (dCOT) and thus highlight changes to the microstructure near tribological FCC alloy surfaces, allowing us to detect subtle differences in lattice orientation and small distances in grain boundary migration. The analysis approach compares computationally generated orientation tomographs with their undeformed counterparts via a simple image analysis filter. We use our visualization method to discuss the acting microstructural mechanisms in a load- and time-resolved fashion, focusing on sliding conditions that lead to twinning, partial lattice rotation, and grain boundary-dominated processes. Extracting and laterally averaging the color saturation value of the generated tomographs allows us to produce quantitative time- and depth-resolved maps that give a good overview of the progress and severity of near-surface deformation. Corresponding maps of the lateral standard deviation in the color saturation show evidence of homogenization processes occurring in the tribologically loaded microstructure, frequently leading to the formation of a well-defined separation between deformed and undeformed regions. When integrated into a computational materials engineering framework, our approach could help optimize material design for tribological and other deformation problems. Graphic Abstract .

36 MATERIALS SCIENCE↗

The Application of Differential Scanning Calorimetry to Investigate Precipitation Behavior in Nickel-Base Superalloys Under Continuous Cooling and Heating Conditions

In this study, a suite of experimental tools and fast-acting, numerical-simulation techniques was used to quantify the precipitation behavior of three nickel-base superalloys: IN-100, LSHR, and 718. Experimental methods comprised differential scanning calorimetry (DSC) to establish the specific heat as a function of temperature and selected direct-resistance heating trials (using a Gleeble ® machine) to obtain samples for microstructural analysis. For the DSC experiments, each alloy was cooled at a prescribed constant rate (between 5 and 20 K/min) after an initial soak/equilibration in the high-temperature, single-phase (supersolvus) temperature regime. On-heating DSC trials beginning at ambient temperature were also performed on alloy 718 in three different starting conditions: super- δ -solvus solution treated and water quenched (denoted as ST), solution treated and aged (STA), and solution treated and overaged (STOA). DSC results, revealing the thermal signatures associated with the kinetics of precipitation of γ ' (IN-100, LSHR) or γ ' and γ " (718), were interpreted using a previously-developed fast-acting routine that treats concurrent nucleation, growth, coarsening, and dissolution. For these simulations, special attention was paid to various thermo-kinetic input parameters including equilibrium solvus-approach curves, bulk free energies of transformation, matrix-precipitate interface energies, and effective diffusivities. For the γ - γ ' superalloys (IN-100 and LSHR), estimates of precipitate volume fraction as a function of temperature from the specific-heat data revealed semi-quantitative agreement with simulation predictions. For the γ - γ '- γ " superalloy (718), simulation predictions of precipitate volume fractions were converted to specific heat as a function of temperature and showed semi-quantitative agreement with the direct measurements.

36 MATERIALS SCIENCE↗

Quantified Differentiation of Surface Topography for Nano-materials As-Obtained from Atomic Force Microscopy Images

Surface texture is an important issue to realize the nature (crest and trough) of surfaces. Atomic force microscopy (AFM) image is a key analysis for surface topography. However, in nano-scale, the nature (i.e., deflection or crack) as well as quantification (i.e., height or depth) of deposited layers is essential information for material scientist. In this paper, a gradient-based K-means algorithm is used to differentiate the layered surfaces depending on their color contrast of as-obtained from AFM images. A transformation using wavelet decomposition is initiated to extract the information about deflection or crack on the material surfaces from the same images. Z-axis depth analysis from wavelet coefficients provides information about the crack present in the material. Using the above method corresponding surface information for the material is obtained. In addition, the Gaussian filter is applied to remove the unwanted lines, which occurred during AFM scanning. Few known samples are taken as input, and validity of the above approaches is shown.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Convolutions on the sphere: commutation with differential operators

We generalize the definition of convolution of vectors and tensors on the 2-sphere, and prove that it commutes with differential operators. Moreover, vectors and tensors that are normal/tangent to the spherical surface remain so after the convolution. These properties make the new filtering operation particularly useful to analyzing and modeling nonlinear dynamics in spherical systems, such as in geophysics, astrophysics, and in inertial confinement fusion applications. An essential tool we use is the theory of scalar, vector, and tensor spherical harmonics. We then show that our generalized filtering operation is equivalent to the (traditional) convolution of scalar fields of the Helmholtz decomposition of vectors and tensors.

42 ENGINEERING↗

Mobility Peak Tailing Reduction in a Differential Mobility Analyzer (DMA) Coupled with a Mass Spectrometer and Several Ionization Sources

The differential mobility analyzer (DMA) is a narrow-band linear ion mobility filter operating at atmospheric pressure. It combines in series with a quadrupole mass spectrometer (Q-MS) for mobility/mass analysis, greatly reducing chemical noise in selected ion monitoring. However, the large flow rate of drift gas (~1000 L/min) required by DMAs complicates the achievement of high gas purity. Additionally, the symmetry of the drying counterflow gas at the interface of many commercial MS instruments, is degraded by the lateral motion of the drift gas at the DMA entrance slit. As a result, DMA mobility peaks often exhibit tails due to the attachment of impurity vapors, either (1) to the reagent ion within the separation cell, or (2) to the analyte of interest in the ionization region. In order to greatly increase the noise-suppression capacity of the DMA, we describe various vapor-removal schemes and measure the resulting increase in the tailing ratio, (TR = signal at the peak maximum over signal two half-widths away from this maximum). Here we develop a low-outgassing DMA circuit connected to a mass spectrometer, and test it with three ionization sources (APCI, Desolvating-nano ESI, and Desolvating low flow SESI). While prior TR values were in the range 100–1000, the three new sources achieve TR ~ 10{sup 5}. The SESI source has been optimized for maximum sensitivity, delivering an unprecedented gain for TNT of 190 counts/fg, equivalent to an ionization efficiency of one out of 140 neutral molecules. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Differential Mobility Spectrometry for Improved Selectivity in Hydrophilic Interaction Liquid Chromatography-Tandem Mass Spectrometry Analysis of Paralytic Shellfish Toxins

Paralytic shellfish toxins (PSTs) are neurotoxins produced by dinoflagellates and cyanobacteria that cause paralytic shellfish poisoning in humans. PST quantitation by LC-MS is challenging because of their high polarity, lability as gas-phase ions, and large number of potentially interfering analogues. Differential mobility spectrometry (DMS) has the potential to improve the performance of LC-MS methods for PSTs in terms of selectivity and limits of detection. This work describes a comprehensive investigation of the separation of 16 regulated PSTs by DMS and the development of highly selective LC-DMS-MS methods for PST quantitation. The effects of all DMS parameters on the separation of PSTs from one another were first investigated in detail. The labile nature of 11α-gonyautoxin epimers gave unique insight into fragmentation of labile analytes before, during, and after the DMS analyzer. Two sets of DMS parameters were identified that either optimized the resolution of PSTs from one another or transmitted them at a limited number of compensation voltage (CV) values corresponding to structural subclasses. These were used to develop multidimensional LC-DMS-MS/MS methods using existing HILIC-MS/MS parameters. In both cases, improved selectivity was observed when using DMS, and the quantitative capabilities of a rapid UPLC-DMS-MS/MS method were evaluated. Limits of detection of the developed method were similar to those without DMS, and differences were highly analyte-dependant. Analysis of shellfish matrix reference materials showed good agreement with established methods. The developed methods will be useful in cases where specific matrix interferences are encountered in the LC-MS/MS analysis of PSTs in complex biological samples. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Broad Separation of Isomeric Lipids by High-Resolution Differential Ion Mobility Spectrometry with Tandem Mass Spectrometry

Maturation of metabolomics has brought a deeper appreciation for the importance of isomeric identity of lipids to their biological role, mirroring that for proteoforms in proteomics. However, full characterization of the lipid isomerism has been thwarted by paucity of rapid and effective analytical tools. A novel approach is ion mobility spectrometry (IMS) and particularly differential or field asymmetric waveform IMS (FAIMS) at high electric fields, which is more orthogonal to mass spectrometry. Here we broadly explore the power of FAIMS to separate lipid isomers, and find a ~75% success rate across the four major types of glycero- and phospho- lipids (sn, chain length, double bond position, and cis/trans). The resolved isomers were identified using standards, and (for the first two types) tandem mass spectrometry. These results demonstrate the general merit of incorporating high-resolution FAIMS into lipidomic analyses. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Maximizing Ion Transmission in Differential Mobility Spectrometry

We provide modeling and experimental data describing the dominant ion-loss mechanisms for differential mobility spectrometry (DMS). Ion motion is considered from the inlet region of the mobility analyzer to the DMS exit, and losses resulting from diffusion to electrode surfaces, insufficient effective gap, ion fragmentation, and fringing field effects are considered for a commercial DMS system with 1-mm gap height. It is shown that losses due to diffusion and radial oscillations can be minimized with careful consideration of residence time, electrode spacing, gas flow rate, and waveform frequency. Fragmentation effects can be minimized by limitation of the separation field. When these parameters were optimized, fringing field effects at the DMS inlet contributed the most to signal reduction. We also describe a new DMS cell configuration that improves the gas dynamics at the mobility cell inlet. The new cell provides a gas jet that decreases the residence time for ions within the fringing field region, resulting in at least twofold increase in ion signal as determined by experimental data and simulations. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Differential Mobility Spectrometry-Mass Spectrometry (DMS-MS) in Radiation Biodosimetry: Rapid and High-Throughput Quantitation of Multiple Radiation Biomarkers in Nonhuman Primate Urine

High-throughput methods to assess radiation exposure are a priority due to concerns that include nuclear power accidents, the spread of nuclear weapon capability, and the risk of terrorist attacks. Metabolomics, the assessment of small molecules in an easily accessible sample, is the most recent method to be applied for the identification of biomarkers of the biological radiation response with a useful dose-response profile. Profiling for biomarker identification is frequently done using an LC-MS platform which has limited throughput due to the time-consuming nature of chromatography. We present here a chromatography-free simplified method for quantitative analysis of seven metabolites in urine with radiation dose-response using urine samples provided from the Pannkuk et al. (2015) study of long-term (7-day) radiation response in nonhuman primates (NHP). The stable isotope dilution (SID) analytical method consists of sample preparation by strong cation exchange-solid phase extraction (SCX-SPE) to remove interferences and concentrate the metabolites of interest, followed by differential mobility spectrometry (DMS) ion filtration to select the ion of interest and reduce chemical background, followed by mass spectrometry (overall SID-SPE-DMS-MS). Since no chromatography is used, calibration curves were prepared rapidly, in under 2 h (including SPE) for six simultaneously analyzed radiation biomarkers. The seventh, creatinine, was measured separately after 2500× dilution. Creatinine plays a dual role, measuring kidney glomerular filtration rate (GFR), and indicating kidney damage at high doses. The current quantitative method using SID-SPE-DMS-MS provides throughput which is 7.5 to 30 times higher than that of LC-MS and provides a path to pre-clinical radiation dose estimation. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Performance Enhancements in Differential Ion Mobility Spectrometry-Mass Spectrometry (DMS-MS) by Using a Modified CaptiveSpray Source

Differential ion mobility spectrometry (DMS) spatially separates ions in the gas phase using the mobility differences of the ions under applied low and high electric fields. The use of DMS as an ion filter (or ion selector) prior to mass spectrometry analysis has been compromised by the limited ion transmission efficiency. This paper reports enhancement of the DMS-MS sensitivity and signal stability using a modified CaptiveSpray™ source. In terms of the ion sampling and transmission efficiency, the modified CaptiveSpray source swept ~ 89% of the ions generated by the tapered capillary through the DMS device (compared to ~ 10% with a conventional microspray source). The signal fluctuation improved from 11.7% (relative standard deviation, RSD) with microspray DMS-MS to 3.6% using CaptiveSpray-DMS-MS. Coupling of LC to DMS-MS via the modified CaptiveSpray source was simple and robust. Using DMS as a noise-filtering device, LC-DMS-MS performed better than conventional LC-MS for analyzing a BSA digest standard. Although LC-DMS-MS had a lower sequence coverage (55%), a higher Mascot score (283) was obtained compared to those of LC-MS (sequence coverage 65%; Mascot score 192) under the same elution conditions. The improvement in the confidence of the search result was attributed to the preferential elimination of noise ions. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

An exploration of pressure dynamics using differential equations defined on a fractal geometry

Pressure tests have been used to understand the behavior of naturally fractured reservoirs (NFRs) by establishing parameters such as permeability, connectivity of fractures, system compressibility, fracture network parameters, and others associated with the physical properties of the reservoir. The complex fracture network of a NFR produces anomalous fluid flow, which is shown by the pressure behavior at the well. A plausible model to explain this behavior is to assume that it arises from a fractal fracture system. However, to estimate the parameters that define this fractal fracture system, fluid flow models based on the modification of Darcy’s law are used. On the other hand, in this work, a fractal structure with known fractal dimension: Sierpinski gasket (SG) is proposed. The objective of this work is to solve numerically the diffusion equation on SG, and establish a comparison with flow models used in the oil industry to investigate the fractality assumption. This study is focused on the qualitative behavior of the solution of the diffusion equation defined on a SG supported by the Kigami’s theory of differential equations on fractals.

42 ENGINEERING↗