Ionic liquid-based deep eutectic solvents as novel solvent-cum-catalyst media for thermal dehydrogenation of chemical hydrides

The current work explores the usage of novel synthesized Deep Eutectic Solvent (DES) as a catalyst cum solvent media for the thermal dehydrogenation of chemical hydrides, namely Ammonia Borane (AB) and Ethylene diamine bisborane (EDAB). In the first instance, the quantum chemistry based COSMO-SAC (COnductor like Screening MOdel Segment Activity Coefficient) model was used for the selection of the pertinent solvent. 1-Butyl-3-methylimidazolium methanesulfonate: Imidazole ([BMIM][MeSO₃]:[Im]) turned out to be an ideal eutectic mixture with the highest predicted solubility with amine boranes. The DES was synthesized by combining the Hydrogen Bond Acceptor (HBA), namely 1-Butyl-3-methylimidazolium methanesulfonate and Imidazole as Hydrogen Bond Donor (HBD) at a molar ratio of 1:2 and T = 70 °C. The formation of DES was confirmed by recording the NMR spectra. Further, the thermal dehydrogenation study was performed at a vacuum of 4 × 10^?2 mbar (gauge pressure) of AB/DES and EDAB/DES systems at 105 °C, where a hydrogen equivalent of 1.40 and 2.55 was produced, respectively. The residual samples were further analyzed through ¹H NMR analysis for the reaction mechanism and to confirm the role of Ionic Liquid-based DES as catalyst cum solvent media.     

Impact of adhesive ingredients on adhesion between rubber and brass-plated steel wire in tire

Proficiency on underlying mechanism of rubber-metal adhesion has been increased significantly in the last few decades. Researchers have investigated the effect of various ingredients, such as hexamethoxymethyl melamine, resorcinol, cobalt stearate, and silica, on rubber-metal interface. The role of each ingredient on rubber-metal interfacial adhesion is still a subject of scrutiny. In this article, a typical belt skim compound of truck radial tire is selected and the effect of each adhesive ingredient on adhesion strength is explored. Out of these ingredients, the effect of cobalt stearate is found noteworthy. It has improved adhesion strength by 12% (without aging) and by 11% (humid-aged), respectively, over control compound. For detailed understanding of the effect of cobalt stearate on adhesion, scanning electron microscopy and energy dispersive spectroscopy are utilized to ascertain the rubber coverage and distribution of elements. X-ray photoelectron spectroscopy results helped us to understand the impact of Cu_XS layer depth on rubber-metal adhesion. The depth profile of the Cu_XS layer was found to be one of the dominant factors of rubber-metal adhesion retention. Thus, this study has made an attempt to find the impact of different adhesive ingredients on the formation of Cu_XS layer depth at rubber-metal interface and establish a correlation with adhesion strength simultaneously.     

HA/β-TCP plasma sprayed coatings on Ti substrate for biomedical applications

The present work focuses on the fabrication of βTCP (β-tricalcium phosphate) and HA/βTCP (hydroxyapatite/β-tricalcium phosphate) composite coatings by plasma spraying. The starting powders were produced via solid-state method using 2 wt% MgO to stabilize βTCP phase. The synthesized powders were preliminarily granulated to be used by the plasma spray process. Coatings obtained on titanium substrates are uniform and well adherent but due to the high temperature and cooling rate typical for plasma spraying process, βTCP phase is almost totally transformed into the α allotrope. Thermal treatment at 800 °C allows the reconversion of the phase αTCP→ βTCP. It is therefore possible to produce coatings with tuneable dissolution properties by selecting the proper initial powder mixture and the specific thermal treatment.     

Prevalence of hepatitis B and C virus infections among haemodialysis patients in Pune (western India)

Vascular injuries may occur as complications of elbow dislocation and usually involve the brachial artery. A case report is presented in which only the radial artery was compromised as a result of the dislocation.     

A new method to estimate parameters of linear compartmental models using artificial neural networks

At present, the preferred tool for parameter estimation in compartmental analysis is an iterative procedure; weighted nonlinear regression. For a large number of applications, observed data can be fitted to sums of exponentials whose parameters are directly related to the rate constants/coefficients of the compartmental models. Since weighted nonlinear regression often has to be repeated for many different data sets, the process of fitting data from compartmental systems can be very time consuming. Furthermore the minimization routine often converges to a local (as opposed to global) minimum. In this paper, we examine the possibility of using artificial neural networks instead of weighted nonlinear regression in order to estimate model parameters. We train simple feed-forward neural networks to produce as outputs the parameter values of a given model when kinetic data are fed to the networks' input layer. The artificial neural networks produce unbiased estimates and are orders of magnitude faster than regression algorithms. At noise levels typical of many real applications, the neural networks are found to produce lower variance estimates than weighted nonlinear regression in the estimation of parameters from mono- and biexponential models. These results are primarily due to the inability of weighted nonlinear regression to converge. These results establish that artificial neural networks are powerful tools for estimating parameters for simple compartmental models.     

A Low-Power Wide-Dynamic-Range Analog VLSI Cochlea

Low-power wide-dynamic-range systems are extremely hard to build. The biological cochlea is one of the most awesome examples of such a system: It can sense sounds over 12 orders of magnitude in intensity, with an estimated power dissipation of only a few tens of microwatts. In this paper, we describe an analog electronic cochlea that processes sounds over 6 orders of magnitude in intensity, and that dissipates 0.5 mW. This 117-stage, 100 Hz to 10 KHz cochlea has the widest dynamic range of any artificial cochlea built to date. The wide dynamic range is attained through the use of a wide-linear-range transconductance amplifier, of a low-noise filter topology, of dynamic gain control (AGC) at each cochlear stage, and of an architecture that we refer to as overlapping cochlear cascades. The operation of the cochlea is made robust through the use of automatic offset-compensation circuitry. A BiCMOS circuit approach helps us to attain nearly scale-invariant behavior and good matching at all frequencies. The synthesis and analysis of our artificial cochlea yields insight into why the human cochlea uses an active traveling-wave mechanism to sense sounds, instead of using bandpass filters. The low power, wide dynamic range, and biological realism make our cochlea well suited as a front end for cochlear implants.     

Calculation of shift of avalanche transit time phase delay due tooptically injected carriers in indium phosphide avalanche diodes

A computer method for the calculation of the phase shift due to optically injected carriers in an InP avalanche transit time diode has been suggested using the numerically simulated negative resistance profiles in the depletion layer of the diode. The results show that the phase shift due to hole injection is larger than that due to electron injection which explains the pronounced effect of photogenerated hole leakage current in modulating the microwave properties of InP diodes