Phosphinoborine Compounds: Mass Spectra and Pyrolysis

The mass spectra of tetramethylphosphinoborine trimer, [P(CH₃)₂B(CH₃)₂]₃ (I) and a a compound, P₅(CH₃)₉B₅H₉, (II) prepared from dimethylphosphinoborine were observed, and the compounds were pyrolyzed at 300 to 500° C. Most peaks in the spectrum of (I) came from the P—B, B—C, and P—C cleavages. The mass spectrum of (II) was much more complicated with evidence for methyl group redistribution.The pyrolysis of both compounds indicates a very complicated mechanism with many unidentifiable compounds. Trends in the formation of volatile products indicate that both compounds are completely decomposed in 4 hr at 450° C. Compound (I) produces trimethylboron, which disappears rapidly above 400° C. Neither (I) nor (II) formed ethane or elemental phosphorus.     

Efficient hybrid EM for linear and nonlinear mixed effects models with censored response

Medical laboratory data are often censored, due to limitations of the measuring technology. For pharmacokinetics measurements and dilution-based assays, for example, there is a lower quantification limit, which depends on the type of assay used. The concentration of HIV particles in the plasma is subject to both lower and upper quantification limit. Linear and nonlinear mixed effects models, which are often used in these types of medical applications, need to be able to deal with such data issues. In this paper we discuss a hybrid Monte Carlo and numerical integration EM algorithm for computing the maximum likelihood estimates for linear and non-linear mixed models with censored data. Our implementation uses an efficient block-sampling scheme, automated monitoring of convergence, and dimension reduction based on the QR decomposition. For clusters with up to two censored observations numerical integration is used instead of Monte Carlo simulation. These improvements lead to a several-fold reduction in computation time. We illustrate the algorithm using data from an HIV/AIDS trial. The Monte Carlo EM is evaluated and compared with existing methods via a simulation study.     

Characterization of superconducting wires and cables by X-ray micro-tomography

Due to their mechanical strength and ability to withstand the large electromagnetic force applied to the superconductors in large magnets during excitation, the Cable-in-Conduit-Conductor (CICC) type superconductors will be employed in the next stage of fusion magnets. Here, we discuss the recent results on the application of a non-invasive method for the characterization of CCIC by X-ray micro-tomography (μXCT). The experiments have been carried out on a high resolution X-ray tomograph in INFLPR (http://tomography.inflpr.ro). An open type nanofocus X-ray source with maximum high voltage of 225 kVp at 15–30 W maximum power and multiple targets of W on different windows materials (Be, Al, Cu or diamond) is the main component. X-rays are detected by means of amorphous silicon flat panel sensor in the cone-beam configuration and high-energy efficient line sensor based on individual scintillators in the fan-beam scanning configuration. The quality of tomographic images (≈40 μm space resolution) allowed the majority of strands of analyzed CICC samples to be fully reconstructed along the investigated segment (up to 300 mm long). Our method provides: (i) local and global void fractions (over a 300 mm length of the sample), (ii) void homogeneity factor as the ratio between void space surface and perimeter and (iii) twist pitch angle of individual strands and its distribution in 3D. It can be used to investigate superconducting CICC during their manufacture, installation or after service inspection, for purposes of QA, characterization or development.     

Quantitative in vivo microsampling for pharmacokinetic studies based on an integrated solid-phase microextraction system

An integrated microsampling approach based on solid-phase microextraction (SPME) was developed to provide a complete solution to highly efficient and accurate pharmacokinetic studies. The microsampling system included SPME probes that are made of poly(ethylene glycol) (PEG) and C18-bonded silica, a fast and efficient sampling strategy with accurate kinetic calibration, and a high-throughput desorption device based on a modified 96-well plate. The sampling system greatly improved the quantitative capability of SPME in two ways. First, the use of the C18-bonded silica/PEG fibers minimized the competition effect from analogues of the target analytes in a complicated sample matrix such as blood or plasma samples, which is a common problem associated with solid coating SPME fibers for quantitative analysis. Moreover, the C18-bonded silica/PEG fibers provide high sensitivity and a large dynamic range that covers the possible sample concentration range during diazepam administration and elimination. Second, the kinetic calibration method offers more accurate quantitation than the calibration curve method for in vivo SPME, because it compensates for convection and matrix effects during sampling. Therefore, it is especially suitable as a fast sampling technique for pre-equilibrium SPME. Furthermore, with the high-throughput desorption device, the integrated system offers compactness and high efficiency. Its feasibility for in vivo sampling was demonstrated by monitoring diazepam pharmacokinetics and validated by conventional chemical assays and equilibrium SPME. In addition, we propose a simple method to determine the apparent distribution constant between an SPME fiber and a blood matix (Kfs) and the distribution constant between an SPME fiber and a pure PBS buffer sample matrix (Kfb). As a result, both total and free concentrations of the drug and its metabolites can be detected simultaneously. Accordingly, the binding constants to the blood matrix can be obtained, which are of special significance for clinical diagnosis and drug discovery.     

Signal Assignment Model for the Memory Management of Multidimensional Signal Processing Applications

Many signal processing systems, particularly in the multimedia and telecom domains, are synthesized to execute data-dominated applications. Their behavior is described in a high-level programming language, where the code is typically organized in sequences of loop nests and the main data structures are multidimensional arrays. Since data transfer and storage have a significant impact on both the system performance and the major cost parameters—power consumption and chip area, the designer must spend a significant effort during the system development process on the exploration of the memory subsystem in order to achieve a cost-optimized design. This paper presents a memory allocation methodology for multidimensional signal processing applications, focusing on the problem of efficiently mapping the multidimensional signals from the algorithmic specification into the physical memory. In a first phase, two previous mapping models are implemented within a common theoretical framework, which is advantageous from both the point of view of computational efficiency and the amount of allocated data storage. Different from all the previous mapping models that aim to optimize the memory sharing between the elements of a same array (creating separate windows in the physical memory for distinct arrays), this proposed mapping model exploit—in a second phase—the possibility of memory sharing between the elements of different arrays. As a consequence, this signal assignment approach yields significant savings in the amount of data storage resulted after mapping.     

Effects of SiO2 and Al2O3 nanofillers on polyethylene properties

Polymers filled with inorganic nanoparticles have become interesting materials as dielectrics because of their improved mechanical and electrical properties compared with the unfilled polymers and with polymer microcomposites. These improvements are mainly due to the large surface area of nanoparticles and new polymer–nanofiller interface characteristics. In the present work, polyethylene nanocomposites with SiO₂ and Al₂O₃ nanoparticles were prepared by melt mixing. Mechanical and electrical properties of these composites were determined and morphological aspects were revealed by scanning electron microscopy, wide‐angle X‐ray diffraction, and atomic force microscopy. The effect of nanostructure and the importance of nanofiller dispersion were analyzed in connection with mechanical and electrical properties. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011     

Characteristics of dynamic brittle fracture captured with peridynamics

Using a bond-based peridynamic model, we are able to reproduce various characteristics of dynamic brittle fracture observed in experiments; crack branching, crack-path instability, asymmetries of crack paths, successive branching, secondary cracking at right angles from existing crack surfaces, etc. We analyze the source of asymmetry in the crack path in numerical simulations with an isotropic material and symmetric coordinates about the pre-crack line. Asymmetries in the order of terms in computing the nodal forces lead to different round-off errors for symmetric nodes about the pre-crack line. This induces the observed slight asymmetries in the branched crack paths. A dramatically enhanced crack-path instability and asymmetry of the branching pattern are obtained when we use fracture energy values that change with the local damage. The peridynamic model used here captures well the experimentally observed successive branching events and secondary cracking. Secondary cracks form as a direct consequence of wave propagation and reflection from the boundaries.     

Percolation network formation in poly(4‐vinylpyridine)/aluminum nitride nanocomposites: Rheological,dielectric, and thermal investigations

This work is concerned with several issues related to the rheological behavior of poly(4‐vinylpyridine)/aluminum nitride (AlN) nanocomposites. The composites are prepared by solution processing combined with ultrasonication and magnetic stirring. To understand the percolated structure, the nanocomposites are characterized via a set of rheological, dielectric, and thermal conductivity analyses. The nanoparticle networks are sensitive to the steady shear deformation particularly at low shear rates, where a shear‐thinning domain is observed. The rheological measurements revealed also that the activation energy is significantly lower at high nanofiller loadings suggesting stronger AlN interactions. The changes in the terminal behavior of shear moduli are the result of variations in composite elasticity determined by the percolation network. The flocculation and percolation thresholds estimated from the rheological moduli dependence on AlN loading are correlated with the dielectric constant values. Thermal conductivity is determined from a new theoretical model involving, besides the contribution of each phase, both percolation processes and the shape of the nanofiller. POLYM. COMPOS., 35:1543–1552, 2014. © 2013 Society of Plastics Engineers     

Surface Modification of Alumina/ Zirconia Ceramics Upon Different Fluoride‐Based Treatments

The aim of this study was to prepare and to characterize the structure of Al₂O₃–3YSZ composites with 5% TiO₂ addition as well as the surface modification upon treatments with SnF₂ and NaBF₄, respectively. SEM micrographs showed the controlled densification of the composites as an effect of 3YSZ and TiO₂ addition to alumina matrix. By FTIR and XRD, the characteristics of Al‐O and Zr‐O vibrations, respectively, the diffractions lines related to α‐corundum and zirconia in tetragonal phase were discussed. Qualitative and quantitative results obtained by XPS and ATR FTIR demonstrated that the proposed materials are more sensitive to SnF₂ than to NaBF₄ treatment.