Synthesis,characterization, rheological and thermal behavior of metallocene ethylene − norbornene copolymers with low norbornene content using pentafluorophenol modified methylaluminoxane

Ethylene ? norbornene copolymers were synthesized using rac‐ethylene bis(indenyl) zirconium dichloride/pentafluorophenol modified methylaluminoxane. First, the effect of using a modifier in combination with a low ratio of Al/Zr on the catalyst activity and co‐monomer incorporation was studied. The results of copolymerization reveal a 20% co‐monomer incorporation improvement and a rise of activity by 2‐fold in the presence of the modifier. Rheological measurements show a higher molecular weight in copolymers synthesized using modified methylaluminoxane. The alternative and dyad block microstructures of copolymers become possible in the case of a norbornene content of more than 14 mol%. Second, the effect of co‐monomer content on the rheological and thermal behavior of the synthesized copolymers was investigated. The results of the rheological study indicate a lower molecular weight in samples containing a higher norbornene content. Dynamic mechanical thermal analysis confirms the influence of different microstructures on the glass transition temperature. The crystal structure of copolymers having a higher molecular weight is emphasized using wide angle X‐ray scattering and DSC even with a greater incorporation of norbornene. © 2015 Society of Chemical Industry     

An Efficient Digital Confidentiality Scheme Based on Commutative Chaotic Polynomial

Multimedia Tools and Applications - One of the most critical aspects of this technologically progressive era is the propagation of information through an unsecured communication channel. The...     

Bi-supported Ziegler–Natta TiCl4/MCM-41/MgCl2 (ethoxide type) catalyst preparation and comprehensive investigations of produced polyethylene characteristics

Bi-supported Ziegler–Natta catalysts (TiCl₄/MCM-41/MgCl₂ (ethoxide type)) were synthesized to improve the morphology and the properties of polyethylene. The morphology control is a crucial issue in polymerization process, while tailoring the properties of polymers is needed for specific applications. The catalysts were synthesized in different ratios of two supports with impregnation method. The polymerization process was carried out in atmospheric slurry reactor. The catalysts were characterized with scanning electron microscopy - energy dispersive X-ray spectroscopy (SEM–EDX), inductively coupled plasma, Fourier transform infrared spectrometry (FTIR), and Brunauer-Emmett-Teller (BET) methods. The polymers were analyzed with scanning electron microscopy (SEM), thermogravimetric analysis (TGA), differential scanning calorimetry, FTIR, and tensile-strength analyses. Ubbelohde viscometer and frequency sweep measurements showed that the synthesized polymers are ultra-high-molecular-weight polyethylene. Mechanical properties of polymers showed higher Young's modulus in samples containing MCM-41, having higher thermal stability supported by TGA analysis. SEM images of bi-supported catalyst showed a controlled spherical morphology with uniform size distribution. SEM analysis support that the polymers replicate their morphology from catalyst, improving their morphology comparing to MgCl₂-supported catalyst. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137, 48553.     

Design and Analysis of New Micromixers Based on Distillation Column Trays

Four passive micromixer designs (G1, G2, G3, and G4) based on distillation columns trays are proposed. The performance of the devices is assessed by numerical simulations. The mixing performance is investigated for different Reynolds numbers and channel heights for oil/ethanol flow. G1 and G4 designs provided a high mixing index. The G1 device achieved superior mixing performance with a moderate pressure drop due to the induced flow recirculation pattern for a relatively high flow rate, highlighting the potential use of such microdevice for scale-up and numbering-up of microdevices in modular chemical plant processing.     

Optimization of a continuous ultrasound assisted oxidative desulfurization (UAOD) process of diesel using response surface methodology (RSM) considering operating cost

A continuous-flow ultrasound-assisted oxidative desulfurization(UAOD) of partially hydro-treated diesel has been investigated using hydrogen peroxide-formic acid as simple and easy to apply oxidation system. The effects of different operating parameters of oxidation stage including residence time(2–24 min), formic acid to sulfur molar ratio(10–150), and oxidant to sulfur molar ratio(5–35) on the sulfur removal have been studied using response surface methodology(RSM) based on Box–Behnken design. Considering the operating costs of the continuous-flow oxidation stage including chemical and electrical energy consumption, the appropriate values of operating parameters were selected as follows: residence time of 16 min, the formic acid to sulfur molar ratio of 54.47, and the oxidant to sulfur molar ratio of 8.24. In these conditions, the sulfur removal and the volume ratio of the hydrocarbon phase to the aqueous phase were 86.90% and 4.34, respectively. By drastic reduction in the chemical consumption in the oxidation stage, the volume ratio of the hydrocarbon phase to the aqueous phase was increased up to 10. Therefore, the formic acid to sulfur molar ratio and the oxidant to sulfur molar ratio were obtained 23.64 and 3.58, respectively, which lead to sulfur removal of 84.38% with considerable improvements on the operating cost of oxidation stage in comparison with the previous works.     

Elliptical slot based polarization insensitive compact and flexible chipless RFID tag

A miniaturized, polarization insensitive, and fully passive chipless radio frequency identification tag is proposed in this research article. The realized tag is based on slotted elliptical structures in a nested loop fashion with identical lengths and widths of slot resonators. Alteration of data sequence is accomplished by addition and elimination of nested resonators in the geometric structure. The tag is capable to encode 10 bits of data and covers spectral range from 3.6 to 15.6 GHz. The formulated structure demonstrates polarization insensitive characteristic. The data encoding structure is analyzed and optimized for different substrates that are, Rogers RT/duroid/5880, Rogers RT/duroid/5870, and Taconic TLX‐0 over the miniaturized footprint of 22.8 × 16 mm². The presented tag is robust, novel, compact, and flexible exhibiting a stable response to impinging electromagnetic waves at various angles of incidence.     

Deep Learning for Accelerated Seismic Reliability Analysis of Transportation Networks

To optimize mitigation, preparedness, response, and recovery procedures for infrastructure systems, it is essential to use accurate and efficient means to evaluate system reliability against probabilistic events. The predominant approach to quantify the impact of natural disasters on infrastructure systems is the Monte Carlo approach, which still suffers from high computational cost, especially when applied to large systems. This article presents a deep learning framework for accelerating seismic reliability analysis, on a transportation network case study. Two distinct deep neural network surrogates are constructed and studied: (1) a classifier surrogate that speeds up the connectivity determination of networks and (2) an end‐to‐end surrogate that replaces modules such as roadway status realization, connectivity determination, and connectivity averaging. Numerical results from k‐terminal connectivity analysis of a California transportation network subject to a probabilistic earthquake event demonstrate the effectiveness of the proposed surrogates in accelerating reliability analysis while achieving accuracies of at least 99%.