Thermo-oxidative aging of high-density polyethylene reinforced with multiwalled carbon nanotubes

The purpose of this study was to investigate the influence of aging on the properties of high-density polyethylene (HDPE) reinforced with multi-wall carbon nanotubes (MWCNTs). Nanocomposites were prepared with nanotubes at 0, 1, 3, and 5 wt%. The long-term durability of the prepared materials was evaluated by thermo-oxidative aging test. Test bodies were aged at 110°C for up to 10 weeks. The nanocomposites were characterized by differential scanning calometry, thermogravimetric analysis (TGA), ¹³C-NMR, elongation at break, and transmission electron microscopy. The aging mainly occurred on the surface of the samples and the neat HDPE showed a strong yellowing after the aging. A strong reduction in elongation at break was seen. For neat HDPE, the elongation at break was reduced from roughly 1400–25%. When HDPE was reinforced with the nanotubes, the reduction was less dramatic.     

Energy relaxation of hot carriers in graphene via plasmon interactions

Energy relaxation of hot carriers in graphene is studied theoretically and experimentally at low temperatures, where the loss rate may differ significantly from that predicted for electron–phonon interactions. We show here that plasmons, important in the relaxation of energetic carriers in bulk semiconductors, can also provide a pathway for energy relaxation in transport experiments in graphene. Reflecting the linear nature of graphene’s bands, we obtain a total loss rate to plasmons that is independent of carrier density. This results in energy relaxation times whose dependence on temperature and density closely matches that reported experimentally.     

Analysis of Cognitive Radio for LTE and 5G Waveforms

Spectrum sensing is one of the major concerns in reaching an efficient Quality of service (QOS) in the advanced mobile communication system. The advanced engineering sciences such as 5G, device 2 device communications (D2D), Internet of things (IoT), MIMO require a large spectrum for better service. Orthogonal frequency division multiplexing (OFDM) is not a choice in advanced radio due to the Cyclic Prefix (CP), wastage of the spectrum, and so on. Hence, it is important to explore the spectral efficient advanced waveform techniques and combine a cognitive radio (CR) with the 5G waveform to sense the idle spectrum, which overcomes the spectrum issue. The demand for spectrum is ever increasing; however, spectrum is limited and is an acutely scarce resource. To alleviate the issue, techniques like Cognitive Radios (CR) have been devised. However, such techniques are non-standardized, and many variations of CR algorithms have been tried and tested. This paper details the several spectrum sensing methods tailored for CR. We explain the benefits, uniqueness, and drawbacks of the various techniques to provide a comprehensive review of the scene, including all recent and novel techniques of CR. Finally, we provided experimental results for the performance of the CR for key 5G and beyond modulation techniques to elaborate the dependency of the CR techniques for CR applications and provide a competitive review of their performance. Experiments show that the CR integrated with NOMA shows better performance as compared with existing techniques.     

Evaluation of surface roughness based on monochromatic speckle correlation using image processing

The measurement of roughness on machined surfaces is of great importance for manufacturing industries as the roughness of a surface has a considerable influence on its quality and function of products. In this paper, an experimental approach for surface roughness measurement based on the coherent speckle scattering pattern caused by a laser beam on the machined surfaces (grinding and milling) is presented. Speckle is the random pattern of bright and dark regions that is observed when a surface is illuminated with a highly or partially coherent light beam. When the illuminating beam is reflected from a surface, the optical path difference between various wavelets with different wavelength would result in interference showing up as a granular pattern of intensity termed as speckle. The properties of this speckle pattern are used for estimation/quantification of roughness parameters. For measurement of surface roughness, initially the speckle patterns formed are filtered in the spatial frequency domain. The optical technique, namely spectral speckle correlation (autocorrelation) is utilized in this work for the measurement of roughness on machined surfaces. It has been observed that the pattern formed is dependent on the roughness of the illuminated surface. For example, a rough surface (milled) shows a small central bright region with a rapid decrease in intensity towards the edges, while a smooth surface (ground) shows a large central bright region with gradually decreasing intensity towards the edges. The complete methodology and analysis for quantification/estimation of surface finish of milled and ground surfaces based on speckle images that could be implemented in practice, is presented in this paper.     

Characterization of multilayer pvd nanocoatings deposited on tungsten carbide cutting tools

The present trends in the coating technologies are gradient coatings, metastable coatings, multicomponaent coatings and multilayer or super lattice coatings. The physical vapour deposition (PVD) process is well-suited technology for these advanced coating technologies. The performance of the coated tools can be improved considerably using multi-layer micro and nanocoatings. The present paper discusses the deposition and characterization of multilayer TiN/Al₂O₃ coatings on cemented tungsten carbide cutting tools using reactive sputtering. The characterization of the coatings was carried out using X-ray diffraction (XRD) for phase analysis, chemical composition using EDAX, adhesion and toughness evaluation using Rockwell indentation test and surface roughness. It was observed that with decrease in thickness of each alumina layer to nanolevel in multilayer coating system results considerable improvement in final surface finish, adhesion and toughness of the coating. The experimental results are presented and analyzed in this paper.     

Characterization of DC magnetron sputtered diamond-like carbon (DLC) nano coating

Development in vapor deposition techniques over the last two decades has led to the introduction of many advanced coatings for metal-cutting tools. This paper examines the characteristics of multilayer Ti, TiN, and diamond-like carbon (DLC) coatings deposited on standard tool substrates at varying sputtering parameters and conditions, such as power density, partial pressure, substrate temperature, and reactive gases. The characteristics of films were examined using an X-ray diffractometer, Raman microscope, surface profilometer (to measure the thickness of the coating), Rockwell hardness tester (to test adhesion), and a micro hardness tester. The pin-on-disc test setup was used to find the coefficient of friction of the coatings. The results indicated that a graded multilayer coating showed better adhesion to the substrates. It was observed that higher target power density resulted in an increase of micro hardness and crystalline planes of coating. Lattice constant matching among layers of coating, proper substrate preparation, and a sequence of cleaning processes are the crucial factors for the enhancement of adhesion strength.     

Thermal stability studies of atmospheric plasma deposited siloxane films deposited on Vycor™ glass

The thermal stability of siloxane films deposited on Vycor glass and silicon substrates using atmospheric pressure plasma was studied. Siloxane films were deposited from a liquid tetraethyl orthosilicate (TEOS) precursor which was nebulised into a helium/oxygen plasma. The thickness of the siloxane films was in the range 1-12 nm as measured using both ellipsometry and X-ray reflectometry. Film composition and chemical properties were examined using Fourier transform infrared spectroscopy and X-ray photoelectron spectroscopy analysis. The thermal stability of the films was evaluated under argon atmosphere at temperatures up to 700 °C. The films were found to exhibit good adhesion without cracks or delamination after the thermal treatment. A decrease in coating thickness and a reduction in surface roughness was however observed indicating, a change in coating chemistry. This was confirmed by the reduction in carbon concentration observed by XPS. Particulates generated by excess gas phase reaction of TEOS were observed on the surface of the coating. A larger reduction in particulates size was observed after thermal treatment compared with the reduction in thickness of the bulk coating. This indicates that the particulates may have a different composition to that of the coating.     

Restoration of blurred images for surface roughness evaluation using machine vision

An attempt is made to evaluate the surface roughness of uniformly moving machined surface (grinding, milling) using machine vision technique. In the case of moving surfaces the images are likely to blur due to the relative motion between the CCD camera and the object to be captured. Hence the degraded image has to be restored by removing distortion due to motion before subsequent analysis. In this work, image blur due to motion is considered, in particular, blur that occurs when the motion is uniform at constant speed and in a fixed direction. The blurred image is modeled as a convolution between the original image and a known point spread function. The Richardson–Lucy Restoration algorithm, a method of estimation based on Bayes theorem has been used to correct the image. The algorithm is tested in simulations and in practical experiments. A simulation gives complete control over the setup and enables to test the performance of the algorithm. The quantification of roughness for restored images are performed using the statistical parameters such as spatial frequency, arithmetic average of gray level and standard deviation after pre-processing. An Artificial Neural Network (ANN) was used with these three statistical parameters as input to predict the vision roughness. Finally, vision roughness values calculated using the deblurred images are compared with the stylus roughness value. An analysis based on the comparison to understand the validity of the present approach of estimation of surface roughness based on the digitally processed images for implementation in practice, is presented in this paper.