Platinum nanoparticles decorated on graphitic carbon nitride-ZIF-67 composite support: An electrocatalyst for the oxidation of butanol in fuel cell applications

In the present study, we report an eco-friendly and simple route to design and synthesize novel nanocomposite catalyst based on platinum nanoparticles anchored on binary support of graphitic carbon nitride (g-C₃N₄) and cobalt-metal-organic framework (ZIF-67). For this purpose, ZIF-67 was prepared by precipitation method and g-C₃N₄ was prepared through thermal polymerization method. Later, ZIF-67 and g-C₃N₄ were hybridized through sonication to get homogeneous g–C₃N₄–ZIF-67 nanocomposite support material. Platinum nanoparticles (PtNPs) were uniformly deposited on g–C₃N₄–ZIF-67 by an electrochemical method. The as-developed nanocatalyst was characterized by morphological, structural and electrochemical techniques. The electrocatalytic activity of PtNPs@g–C₃N₄–ZIF-67 nanocatalyst towards butanol oxidation was evaluated via CV, CA, LSV and EIS in an alkaline medium. Results revealed that the proposed catalyst showed greatly enhanced electrooxidation of butanol in terms of high magnificent current density, lower oxidation potential, excellent long-term stability, large surface area, low charge transfer resistance and less toxic ability. Enhanced catalytic performance of the proposed catalyst could be ascribed to the synergistic effect of g–C₃N₄–ZIF-67 nanocomposite and PtNPs. The PtNPs@g–C₃N₄–ZIF-67 catalyst holds promising potential applications to be used as an anodic electrocatalyst for the development of high-performance alkaline fuel cells.     

Cooperative Diversity in Secondary Systems: Efficient Relaying Protocol for Cognitive Radio

Wireless Personal Communications - This paper considers half-duplex cooperative spectrum sharing scheme where both primary and secondary systems mutually cooperate with each other to exploit...     

Rheological behavior of neat and carbon fiber-reinforced poly(ether ketone ketone) for extrusion deposition additive manufacturing

To develop new materials for extrusion additive manufacturing (AM) systems, a fundamental understanding of rheological properties is essential to correlate the effect of processing on material structure and its properties. In this work, the rheological properties of five different grades of neat and carbon fiber (CF)-reinforced poly(ether ketone ketone) are reported. Rheological properties are essential to understand the effect of reinforcing fibers and AM process parameters such as time, temperature, environment, and shear rate on flow behavior during processing. Small-amplitude oscillatory shear tests and steady shear tests indicated neat grades to exhibit less increase in viscosity over time when processed in air than the CF-filled grades. The filled grades showed greater shear thinning and lower sensitivity to temperature. Overall, this rheological analysis provides a broad framework for determining appropriate processing conditions for extrusion deposition AM of such high-temperature polymer systems.     

Features of ultrasonic wave propagation to identify defects in composite materials modelled by finite element method

A two-dimensional plane strain finite element model with absorbing boundary condition has been developed to investigate the ultrasonic wave propagation in isotropic and orthotropic media. It is capable of simulating the experimental pulse echo technique to obtain A-scan data, when a short duration pulse is transmitted into a domain with or without a flaw. The flaw can either be a crack or an inclusion of different material such as a Teflon insert or a resin rich zone. After performing FFT on the A-scan data, frequency domain feature analysis is done. The study provides a guideline regarding the suitability of certain harmonics sensitive to certain types of flaw. The simulation shows other important artifacts of wave propagation such as mode conversion and scattering due to the presence of flaws.     

Structural and electrical measurements of CdZnSe composite

TheI—Vcharacterization and the electrical resistivity of selenium rich Se₈₅Cd_15-xZn_x (x = 0, 3, 7, 11 and 15) system at room temperature have been studied. Samples were obtained using melt cooling technique. So prepared samples were then characterized in terms of their crystal structure and lattice parameter using X-ray diffraction method. The materials were found to be poly crystalline in nature, having zinc blend structure over the whole range of zinc concentration. The measurements ofI—V bdcharacteristics have been carried out at different temperatures from room to 140°C. The electrical resistivity of the samples with composition at room temperature has been found to vary between maximum 2.7 x 10⁸ Ωm and minimum 7.3 x 10⁵ Ωm and shows a maximum at 3 at. wt.% of Zn. The carrier activation energy of the samples with composition has also been determined and found to vary from 0.026 eV to 0.111 eV.     

Deceleration of a porous rotating disk in a viscous fluid

The flow due to a rotating disk decelerating with an angular velocity inversely proportional to time with either surface suction (or injection) which again varies with time is investigated. The unsteady Navier-Stokes equations are transformed to non-linear ordinary differential equations using similarity transformations. The resulting equations are solved numerically using a globally convergent homotopy method. The flow depends on two non-dimensional parameters, namely an unsteadiness parameter $\text{S}$ and a suction (or injection) parameter $\text{A}$. Some interesting numerical results are presented graphically and discussed.     

Short‐beam three‐point bend test study in syntactic foam. Part III: Effects of interface modification on strength and fractographic features

Syntactic foam slabs having uncoated microballoons and paraffin oil surface‐treated microballoons were fabricated and tested for short‐beam three‐point bend test. The work points to the role of paraffin oil coating first weakening the interface between the microballoons and the matrix and hence lowering the efficiency of load transfer from matrix to the fillers (i.e., microballoons). This led to an overall decrement of 71% in the experimentally measured strength value compared to the deduced value for uncoated microballoons' specimens. The large strengths for uncoated microballoons specimens can be traced to the presence of the curvilinear marks in the matrix that, incidentally, are absent in the case of paraffin oil coated specimens. These observations are revealed distinctly in the microscopy of test‐failed specimens. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 98: 687–693, 2005     

Short beam three point bend tests in syntactic foams. Part I: Microscopic characterization of the failure zones

Scanning Electron Microscopic (SEM) studies were carried out on the failure surface of syntactic foam material tested in a short beam three point bend test (SBT) by employing 21 × 15 × 3 mm³ dimension bearing specimens. The syntactic foams were fabricated using glass microballoons in epoxy binder. The failure of the tensile, compression, and shear dominated regions were studied by SEM at different magnifications. The tensile region had characteristic features, such as partial debonding of the microballoons from the matrix and cracking of glass microballoons, apart from matrix cracking and some river pattern features. The compression side was characterized by crushing and collapsing of microballoons, resulting in accumulation of debris with no apparent river pattern for matrix‐rich regions. The midway positions of the SBT failed surface comprised of deformation bands in the matrix and occasional debonding of microballoons. The morphology recorded in the tensile and compression regions corroborated well with the results obtained on these foam samples in those specimens that were subjected to pure uniaxial tension and compression, respectively. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 98: 673–679, 2005     

Observer-invariant histopathology using genetics-based machine learning

Prostate cancer accounts for one-third of noncutaneous cancers diagnosed in US men and is a leading cause of cancer-related death. Advances in Fourier transform infrared spectroscopic imaging now provide very large data sets describing both the structural and local chemical properties of cells within prostate tissue. Uniting spectroscopic imaging data and computer-aided diagnoses (CADx), our long term goal is to provide a new approach to pathology by automating the recognition of cancer in complex tissue. The first step toward the creation of such CADx tools requires mechanisms for automatically learning to classify tissue types—a key step on the diagnosis process. Here we demonstrate that genetics-based machine learning (GBML) can be used to approach such a problem. However, to efficiently analyze this problem there is a need to develop efficient and scalable GBML implementations that are able to process very large data sets. In this paper, we propose and validate an efficient GBML technique——based on an incremental genetics-based rule learner. exploits massive parallelisms via the message passing interface (MPI) and efficient rule-matching using hardware-implemented operations. Results demonstrate that is capable of performing prostate tissue classification efficiently, making a compelling case for using GBML implementations as efficient and powerful tools for biomedical image processing.