Enhancement of electrical resistivity of Sr0.5Ba0.5Fe12O19 nanomaterials by doping with lanthanum and nickel

From the viewpoint of electronic and telecommunication devices, the electrical resistivity is required to be high to curb the eddy current losses for efficient performance at high frequencies. In the present work, Sr_0.5Ba_0.5Fe₁₂O₁₉ hexaferrite has been doped with a binary mixture of lanthanum and nickel using chemical co-precipitation method of synthesis. The crystallite size of the synthesized samples is estimated in the range of 36–58 nm and their structural analyses have confirmed a single magnetoplumbite phase. The magnitude of the dc-electrical resistivity is enhanced, by almost 100 times, but Curie temperature (T_C) is reduced by doping with La–Ni, which has been explained on the basis of the exchange interactions. In addition, the doped samples exhibit very low dielectric constant (έ = 11–13) and low dielectric loss tangent (tan δ = 0.07–0.10) determined at a frequency of 1 MHz. These characteristics may be suitable for their potential application in electromagnetic attenuation materials and microwave devices.     

Plasma-enhanced chemical vapor deposition of polyperinaphthalene thin films

Plasma-enhanced chemical vapor deposition (PECVD) has been used to grow corrosion-resistive, semiconducting thin films of the graphite-like polymer polyperinaphthalene (PPN) from 3,4,9,10-perylenetetracarboxylic dianhydride (PTCDA). Unlike thermal chemical vapor deposition of PPN from PTCDA, where thin film growth is catalyzed by a transition metal substrate, PPN films have been grown by PECVD for the first time on non-catalytic substrates: indium tin oxide (ITO)-coated glass, aluminum and silicon. Films with the same morphology and molecular characteristics have also been grown on steel substrates, where iron functions as a growth catalyst. Potentiodynamic corrosion measurements in pH 5 water show that PPN films on steel provide an effective corrosion protection layer.     

Pearlite determination in plain carbon steel by eddy current method

Eddy current method has been used for the evaluation of pearlitic microstructure in low to high plain carbon steels. Plain carbon steel samples were heat treated in a furnace. Half of these were slowly cooled in the furnace and half in the air. This resulted in different pearlitic microstructures in the samples. Eddy current readings for all the samples were recorded and studied. It was found that eddy current measurement can be used for obtaining reliable and quick detection of pearlitic percentage in plain carbon steels.     

Vibration characteristics of FGM circular cylindrical shells using wave propagation approach

In this paper, the wave propagation approach is employed to study the vibration characteristics of functionally graded material circular cylindrical shells. Axial modal dependence is approximated by exponential functions. This is a very simple and easily applicable technique. This avoids a large amount of algebraic manipulations. A theoretical analysis of shell natural frequencies are conducted for various boundary conditions. Validity and accuracy of the present method are confirmed by comparing the present results with those available in the literature. A good agreement is observed between the two sets of the results.     

Immobilization of Trichoderma viride for enhanced methylene blue biosorption: Batch and column studies

An efficient dye biosorbent was developed by entrapping a fungus mold, Trichoderma viride, within loofa sponge (LS) matirx. Immobilization enhanced the sorption of dye by 30% at equilibrium as compared with T. viride free biomass (TVFB). The maximum dye biosorption capacity of T. viride immobilized onto loofa sponge (TVILS) and TVFB was found to be 201.52 and 155.06 mg g⁻¹ biomass, respectively. The kinetics of dye removal by TVILS was rapid, with 84.3% sorption within the first 30 min and equilibrium after 90 min, whereas sorption by TVFB was slower as 61.4% dye was removed in first 30 min and equilibrium was achieved in 120 min. Biosorption kinetics and equilibria followed the pseudo-second-order and Langmuir adsorption models. FTIR spectroscopy of T. viride biomass showed that amine, hydroxyl, carbonyl and amide bonds were involved in the sorption of dye. Dye desorption from dye-laden TVILS with 0.1 M HCl was 99%. Regenerated TVILS was reusable without any appreciable decrease in its biosorption capacity during five repeated cycles. The dye removing capacity of TVILS in a continuous-flow column bioreactor was better than in batch-scale procedures. The study shows that TVILS has the potential of application as an efficient biosorbent for the removal of methylene blue from aqueous solutions.     

Determination of Temperature Dependence of Electrical Conductivity and Its Relationship with Ionic Strength of Anaerobic Digester Supernatant, for Struvite Formation

Electrical conductivity (EC) is used for monitoring different types of aqueous systems. The measured EC value at any temperature needs to be corrected for a standard temperature, for reporting or comparison, since EC is dependent on temperature. A temperature compensation factor has been derived for conductivity correction from anaerobic digester supernatant/centrate samples of five different wastewater treatment plants in western Canada. For a temperature compensation factor of 0.0198°C?1, corresponding to the standard temperature at 25°C, the estimated EC25 values were found to be reasonably accurate, with a maximum error of 2.01%. The estimated EC values, based on any standard temperature, were found to be statistically similar to each other. Considering the temperature dependence of EC, a relationship between EC and ionic strength was developed in this study for anaerobic digester supernatant/centrate samples. This relationship can be used to estimate the ionic strength of the solution in a system associated with struvite formation from anaerobic digester supernatant/centrate and effectively monitor the system performance.     

Chemical Coupled PEDOT:PSS/Si Electrode: Suppressed Electrolyte Consumption Enables Long‑Term Stability

Huge volume changes of Si during lithiation/delithiation lead to regeneration of solid-electrolyte interphase(SEI)and consume electrolyte.In this article,γ-glycidoxypropyl trimethoxysilane(GOPS)was incorporated in Si/PEDOT:PSS electrodes to construct a flexible and conductive artificial SEI,effectively suppressing the consumption of electrolyte.The optimized electrode can maintain 1000 mAh g^−1 for nearly 800 cycles under limited electrolyte compared with 40 cycles of the electrodes without GOPS.Also,the optimized electrode exhibits excellent rate capability.The use of GOPS greatly improves the interface compatibility between Si and PEDOT:PSS.XPS Ar+etching depth analysis proved that the addition of GOPS is conducive to forming a more stable SEI.A full battery assembled with NCM 523 cathode delivers a high energy density of 520 Wh kg^−1,offering good stability.     

Optimization of abrasive water jet cutting of ductile materials

Full factorial design of experiments was developed in order to investigate the effects of jet pressure, abrasive mixing rate, cutting feed, and plate thickness upon three response variables, surface finish of cutting wear zone, percentage proportion of striation free area, and maximum width of cut. The set of sixteen experiments was performed on each of the following two ductile materials: AISI 4340 (high strength low alloy steel, hardened to 49HRc) and Aluminum 2219. Analysis of Variance (ANOVA) was performed on experimental data in order to determine the significance of effects of different parameters on the performance measures. It was found that cutting feed and thickness were highly influential parameters, while abrasive mixing rate is influential upon surface roughness only. Strong interaction was found between jet pressure and workpiece material. Multi-criteria numerical optimization was performed in order to simultaneously maximize/minimize different combinations of performance measures.     

Adsorption of dyes from aqueous solutions on activated charcoal

Adsorption of industrially important dyes namely bromophenol blue, alizarine red-S, methyl blue, methylene blue, eriochrome black-T, malachite green, phenol red and methyl violet from aqueous media on activated charcoal has been investigated. The effect of shaking time, pH and temperature on the adsorption behaviour of these dyes has been studied. It was noted that adsorption of all the dyes on activated charcoal decreases with an increase in the pH and the temperature. The adsorption isotherms at different temperatures were found to be of L-type. Adsorption data was fitted to Freundlich, BET and Langmuir isotherms and various adsorption parameters have been calculated. The thermodynamic parameters such as DeltaG, DeltaH and DeltaS were calculated from the slopes and intercepts of the linear variation of lnK against 1/T, where K is the adsorption coefficient obtained from Langmuir equation, was used. The calculated values for the heat of adsorption and the free energy indicate that adsorption of dyes is favored at low temperatures and the dyes are chemisorbed on activated charcoal.     

Autonomous Parking-Lots Detection with Multi-Sensor Data Fusion Using Machine Deep Learning Techniques

The rapid development and progress in deep machine-learning techniques have become a key factor in solving the future challenges of humanity. Vision-based target detection and object classification have been improved due to the development of deep learning algorithms. Data fusion in autonomous driving is a fact and a prerequisite task of data preprocessing from multi-sensors that provide a precise, well-engineered, and complete detection of objects, scene or events. The target of the current study is to develop an in-vehicle information system to prevent or at least mitigate traffic issues related to parking detection and traffic congestion detection. In this study we examined to solve these problems described by (1) extracting region-of-interest in the images (2) vehicle detection based on instance segmentation, and (3) building deep learning model based on the key features obtained from input parking images. We build a deep machine learning algorithm that enables collecting real video-camera feeds from vision sensors and predicting free parking spaces. Image augmentation techniques were performed using edge detection, cropping, refined by rotating, thresholding, resizing, or color augment to predict the region of bounding boxes. A deep convolutional neural network F-MTCNN model is proposed that simultaneously capable for compiling, training, validating and testing on parking video frames through video-camera. The results of proposed model employing on publicly available PK-Lot parking dataset and the optimized model achieved a relatively higher accuracy 97.6% than previous reported methodologies. Moreover, this article presents mathematical and simulation results using state-of-the-art deep learning technologies for smart parking space detection. The results are verified using Python, TensorFlow, OpenCV computer simulation frameworks.