Electrorheological behavior of low filled suspensions of highly anisometric montmorillonite particles

The electrorheological (ER) behavior of modified montmorillonite (MMT) suspensions in polydimethylsiloxane is studied. As established by rotational viscometry, the samples with a dispersed phase concentration from 1 to 8 wt % reveal viscous Newtonian behavior and dramatically change their properties to elastic when electric field is applied. The rheological characteristics of the suspensions over 0–7 kV mm⁻¹ range of electric field strengths are also studied. Novel X-ray diffraction method is developed to evaluate the suspension of the filler in a siloxane medium and to calculate the degree of its exfoliation. The dependence of exfoliation degree, dielectric, and ER characteristics on the type of modifier in the MMT structure is considered. Based on the obtained data, a new model of system behavior with the various types of fillers is proposed and the prospects of utilizing MMT as a filler for ER fluids are demonstrated. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47678.     

New developments in flame retardancy of styrene thermoplastics and foams

This review provides an insight into new developments in flame retardancy of the broad class of styrenic polymers but mostly focuses on commercially important styrene thermoplastics, on some blends based on polystyrene as well as on polystyrene foams. Although halogen‐based systems continue to dominate in flame retardancy of styrenic polymers, various alternative systems are being developed. Especially, activity is observed with phosphorus‐based flame retardants, where some systems are already commercially available. There is also significant activity with nanocomposites, where good results in retarding flame spread have been achieved, but the problem of ignition resistance has not been solved yet. Critical discussion of various flame‐retardant systems developed for styrenics is given. Copyright © 2007 Society of Chemical Industry     

Coupled experimental and thermodynamic study of the Zn-Fe-Si-O system

Experimental and thermodynamic modeling studies have been carried out on the Zn-Fe-Si-O system. This research is part of a wider program to characterize zinc/lead industrial slags and sinters in the PbO-ZnO-SiO₂-CaO-FeO-Fe₂O₃ system. Experimental investigations involve high-temperature equilibration and quenching techniques followed by electron probe X-ray microanalysis (EPMA). Liquidus temperatures and solid solubilities of the crystalline phases were measured in the temperature range from 1200 °C to 1450 °C (1473 to 1723 K) in the zinc ferrite, zincite, willemite, and tridymite primary-phase fields in the Zn-Fe-Si-O system in air. These equilibrium data for the Zn-Fe-Si-O system in air, combined with previously reported data for this system, were used to obtain an optimized self-consistent set of parameters of thermodynamic models for all phases.     

Generation

The structure and function of the target-language generation module for KBMT-89 is described. The lexical selection module (which includes thematic-role subcategorization, a meaning distance metric, and syntactic subcategorization) is presented. We also describe the generation mapping rules, and rule interpretation in the generation of f-structures for target language utterances.     

Local Phenomena in Oxides by Advanced Scanning Probe Microscopy

In the last two decades, scanning probe microscopies (SPMs) have become the primary tool for addressing structure and electronic, mechanical, optical, and transport phenomena on the nanometer and atomic scales. Here, we summarize basic principles of SPM as applied for oxide materials characterization and present recent advances in high-resolution imaging and local property measurements. The use of advanced SPM techniques for solutions of material related problems is illustrated on the examples of grain boundary transport in polycrystalline oxides and ferroelectric domain imaging and manipulation. Future prospects for SPM applications in materials science are discussed.     

Properties of single-walled carbon nanotube-based aerogels as a function of nanotube loading

Here, we present the synthesis and characterization of low-density single-walled carbon nanotube-based aerogels (SWNT-CA). Aerogels with varying nanotube loading (0–55 wt.%) and density (20–350 mg cm^?3) were fabricated and characterized by four-probe method, electron microscopy, Raman spectroscopy and nitrogen porosimetry. Several properties of the SWNT-CAs were highly dependent upon nanotube loading. At nanotube loadings of 55 wt.%, shrinkage of the aerogel monoliths during carbonization and drying was almost completely eliminated. Electrical conductivities are improved by an order of magnitude for the SWNT-CA (55 wt.% nanotubes) compared to those of foams without nanotubes. Surface areas as high as 184 m² g^?1 were achieved for SWNT-CAs with greater than 20 wt.% nanotube loading.     

3D thermohydrodynamic analysis of a textured slider

Analysis of a 3D inlet textured slider bearing with a temperature dependent fluid is performed. Numerical simulations are carried out for a laminar and steady flow. Hot and cold lubricant mixing in the groove is modelled and examined for different operating conditions. Thermohydrodynamic performance of the bearing is analyzed for different texture lengths.Results show that texture has a stronger and positive influence on load carrying capacity when thermal effects are considered. This beneficial effect is at a maximum for the longest dimples with a length shorter than the pad length. Texture is also beneficial for the load carrying capacity when the sliding speed and inlet flow rate are varied. The load carrying capacity of the slider can be increased by up to 16% in severe operating conditions (high sliding speed).     

Conductometric biosensor based on glucose oxidase and beta-galactosidase for specific lactose determination in milk

This paper investigates the development of a biosensor associating two distinct enzymatic activities, that of the beta-galactosidase and that of the glucose oxidase, in order to apply it for the quantitative detection of lactose in milk. To eliminate interferences with glucose, a differential mode of measurement was used. Results show a linear calibration curve for lactose concentration between 60 and 800 μM (0.03 to 0.3 g/L). Tests with real commercial milk samples were carried out to validate the conductometric biosensor.     

A microwave transmission-line network guiding electromagnetic fields through a dense array of metallic objects

We present measurements and simulations of a transmission-line network that has been designed for cloaking applications in the microwave region. Here the network is not used for cloaking but for channelling electromagnetic fields through an electrically dense array of metal objects, which alone is basically impenetrable to the impinging electromagnetic radiation. With the designed transmission-line network the waves emitted by a source placed in an air-filled waveguide are coupled into the network and guided through the array of metallic objects. Our goal is to illustrate the simple manufacturing, assembly, and the general feasibility of cloaking devices based on the transmission-line approach. Most importantly, we demonstrate both with measurements and with numerical simulations the excellent coupling of waves between the network and the surrounding medium.     

Learning and Predicting Photonic Responses of Plasmonic Nanoparticle Assemblies via Dual Variational Autoencoders

The application of machine learning is demonstrated for rapid and accurate extraction of plasmonic particles cluster geometries from hyperspectral image data via a dual variational autoencoder (dual-VAE). In this approach, the information is shared between the latent spaces of two VAEs acting on the particle shape data and spectral data, respectively, but enforcing a common encoding on the shape-spectra pairs. It is shown that this approach can establish the relationship between the geometric characteristics of nanoparticles and their far-field photonic responses, demonstrating that hyperspectral darkfield microscopy can be used to accurately predict the geometry (number of particles, arrangement) of a multiparticle assemblies below the diffraction limit in an automated fashion with high fidelity (for monomers (0.96), dimers (0.86), and trimers (0.58). This approach of building structure-property relationships via shared encoding is universal and should have applications to a broader range of materials science and physics problems in imaging of both molecular and nanomaterial systems.