Tractive rolling contact mechanics of graded coatings

In this study, the tractive rolling contact problem between a rigid cylinder and a graded coating is investigated. The main objective of this study is to investigate the effect of the stiffness ratio, the coefficient of friction and the coating thickness on the surface contact tractions, the surface in-plane stress, the stick zone length and the creep ratio parameter that may have a bearing on the fatigue life of the component. Assuming that the shear modulus varies exponentially through the thickness of the coating, the governing integral equations associated with the rolling contact problem are constructed. Furthermore, it is supposed that the contact patch is controlled by a central stick zone accompanied by two slip zones. The conventional Goodman approximation is employed in order to decouple the governing singular integral equations. Finally, the numerical solution of the integral equations is obtained by applying the Gauss–Chebyshev integration method.     

Synthesis,photophysical and antioxidant properties of pyrrolo[3,2-c]carbazole and dipyrrolo[3,2-c:2′,3′-g]carbazole compounds

Research on Chemical Intermediates - The synthesis of (6-ethyl-1,6-dihydropyrrolo[3,2-c]carbazol-2-yl)methanol 5 and...     

A Boron Doped Diamond Electrode Modified with Nano‐carbon Black for the Sensitive Electrochemical Determination of Chlorogenic Acid

An electrochemical method was developed for the sensitive determination of chlorogenic acid using a boron doped diamond electrode (BDDE) modified with nano‐carbon black (nano‐CB). The active surface areas were found to be 0.059 and 0.146 cm² for the unmodified BDDE, and nano‐CB/BDDE, respectively. Compared with a BDDE, the nano‐CB/BDDE exhibited a well‐defined redox couple for chlorogenic acid. In addition, the plot of the peak current response changing from a square root to a linear dependence on scan rate is attributed to the transition from planar diffusion to surface behaviour. The anodic and cathodic peak separations (ΔE_p) were 97 mV and 14 mV at BDDE and nano‐CB/BDDE, respectively. The decrease in ΔE_p at the proposed electrode indicated that the process of chlorogenic acid was greatly accelerated. Square wave voltammetry (SWV) exhibited a dynamic range in which the current versus the concentration of chlorogenic acid were linear from 2.0×10^?8 to 2.0×10^?6 M with a LOD of 4.1×10^?9 M (based on 3S_b/m). The nano‐CB modified BDDE provided improved electrochemical behavior, high electrocatalytic activity, high sensitivity and good reproducibility.     

Determination of thermal conductivities of Sn–Zn lead-free solder alloys with radial heat flow and Bridgman-type apparatus

The variations of thermal conductivities of solid phases versus temperature for pure Sn, pure Zn and Sn–9 wt.% Zn, Sn–14 wt.% Zn, Sn–50 wt.% Zn, Sn–80 wt.% Zn binary alloys were measured with a radial heat flow apparatus. The thermal conductivity ratios of liquid phase to solid phase for the pure Sn, pure Zn and eutectic Sn–9 wt.% Zn alloy at their melting temperature are found with a Bridgman-type directional solidification apparatus. Thus, the thermal conductivities of liquid phases for pure Sn, pure Zn and eutectic Sn–9 wt.% Zn binary alloy at their melting temperature were evaluated by using the values of solid phase thermal conductivities and the thermal conductivity ratios of liquid phase to solid phase.     

Hexagonal Type Ising Nanowire with Spin-1 Core and Spin-2 Shell Structure

Thermodynamic properties and phase diagrams of a mixed spin-(1,2) Ising ferrimagnetic system with single ion anisotropy on hexagonal nanowire are studied by using effective-field theory with correlations. The susceptibility, internal energy and specific heat of the system are numerically examined and some interesting phenomena in these quantities are found. The effect of the Hamiltonian parameters on phase diagrams are examined in detail. Besides second-order phase transition, lines of first-order transition and tricritical points are found. In particular, we found that for some negative values of single-ion anisotropies, there exist first-order phase transitions.     

Numerical investigation of BB-AMR scheme using entropy production as refinement criterion

In this work, a parallel finite volume scheme on unstructured meshes is applied to fluid flow for multidimensional hyperbolic system of conservation laws. It is based on a block-based adaptive mesh refinement strategy which allows quick meshing and easy parallelisation. As a continuation and as an extension of a previous work, the useful numerical density of entropy production is used as mesh refinement criterion combined with a local time-stepping method to preserve the computational time. Then, we numerically investigate its efficiency through several test cases with a confrontation with exact solution or experimental data.     

Complexiton solutions for two nonlinear partial differential equations via modification of simplified Hirota method

In this study, we obtain complexiton solutions of Sawada–Kotera equation and ninth-order KdV equation. For this cause, we employ Wazwaz and Zhaqilao’s method which can be regarded as generalization of simplified Hirota method through extension real parameters into complex parameters. Special conditions to distinguish complexiton, soliton, and soliton–complexiton interaction solutions from each other are given.     

Brain Inspired Cortical Coding Method for Fast Clustering and Codebook Generation

Highlights What are the main findings?

• A cortical coding method is developed inspired by the network formation in the brain, where the information entropy is maximized while dissipated energy is minimized.
• The execution time in the cortical coding model is far superior, seconds versus minutes or hours, compared to those of the frequently used current algorithms, while retaining comparable distortion rate.

What is the implication of the main finding?

• The significant attribute of the methodology is its generalization performance, i.e., learning rather than memorizing data.
• Although only vector quantization property was demonstrated herein, the cortical coding algorithm has a real potential in a wide variety of real-time machine learning implementations such as , temporal clustering, data compression, audio and video encoding, anomaly detection, and recognition, to list a few.

AbstractA major archetype of artificial intelligence is developing algorithms facilitating temporal efficiency and accuracy while boosting the generalization performance. Even with the latest developments in machine learning, a key limitation has been the inefficient feature extraction from the initial data, which is essential in performance optimization. Here, we introduce a feature extraction method inspired by energy–entropy relations of sensory cortical networks in the brain. Dubbed the brain-inspired cortex, the algorithm provides convergence to orthogonal features from streaming signals with superior computational efficiency while processing data in a compressed form. We demonstrate the performance of the new algorithm using artificially created complex data by comparing it with the commonly used traditional clustering algorithms, such as Birch, GMM, and K-means. While the data processing time is significantly reduced—seconds versus hours—encoding distortions remain essentially the same in the new algorithm, providing a basis for better generalization. Although we show herein the superior performance of the cortical coding model in clustering and vector quantization, it also provides potent implementation opportunities for machine learning fundamental components, such as reasoning, anomaly detection and classification in large scope applications, e.g., finance, cybersecurity, and healthcare.     

Measurement of the Antipsychotic Clozapine Using Reduced Graphene Oxide Nanocomposites-Au/Pd/Pt Electrodes

Enhanced methods of drug monitoring are required to support the individualization of therapeutic drug dosing. Clozapine is one of the most important medications for managing schizophrenia, and timely measurement of serum clozapine levels has been identified as a barrier to the broader use of clozapine. For the first time, reduced graphene oxide nanocomposites were used to construct an electrochemical clozapine (Clz) sensor. The Reduced graphene oxide (Rego) nanocomposites were synthesized and characterized by using X-Ray Diffraction (XRD), Fourier-Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM), and Transmission Electron Microscopy (TEM) techniques. The Clz sensing electrode was fabricated by drop coating of Rego nanocomposites suspension and Nafion solution on the pencil graphite electrode, respectively. The electrochemical behavior and influence of various physicochemical parameters of sensing electrodes were investigated by using cyclic voltammetry (CV) and differential voltammetry (DPV) techniques. The designed sensor displayed decent linear range, detection limit, reproducibility, and reusability results. Under optimum experimental parameters a linear dynamic range of 0.05–10 μM clozapine was observed with actual detection limit of 50 nM. Furthermore, the designed sensing electrode was used to measure the amount of Clz in real samples.     

Synthesis and X-ray crystal structure determination of N-p-methylphenyl-4-benzoyl-3,4-diphenyl-2-azetidinone

The title compound, C₂₉H₂₃NO₂, has been characterized by single-crystal X-ray diffraction at two different temperatures (303 K and 120 K) and wavelengths (MoK _α and CuK _α). The non-centrosymmetric hexagonal crystal structure contains four-membered planar β-lactam ring with an unusually long C-C bond. The β-lactam ring is almost planar.