Spherulitic formation and characterization of partially fluorinated copolymers and their nanohybrids with functional fillers

Poly[vinylidenefluoride‐co‐(tetrafluoroethylene)] (P(VDF‐TeFE)) exhibited clear spherulitic texture with negative birefringence. The number and growth rates of the spherulites decreased at high crystallization temperature than at low crystallization temperature. Nonetheless, overall larger spherulites were found at high crystallization temperature and the brightness of the spherulites increased very fast at low crystallization temperature, thereafter it seemed as diminution of birefringence. AFM was used to investigate the impact of organo modified nanodiamond(ND) on spherulitic textures, lamellar thickness, and thickness distribution of P(VDF‐TeFE) copolymer. Poly[ethylene‐co‐(tetrafluoroethylene)] (ETFE) also confirmed spherulites structure and the boundaries could be clearly observed. By incorporation of the organo modified nanodiamond (ND) and organo‐modified montmorillonite (MMT) in fluropolymer matrix, it was found that spherulitic texture was seriously disordered and their nanohybrids was found only to have poorly developed spherulite structure. Both of the nanohybrids samples show better crystallization temperature as compared to their neat copolymer samples. Furthermore, the incorporation of nanoparticles decreased the size of the spherulites. POLYM. ENG. SCI., 57:161–171, 2017. © 2016 Society of Plastics Engineers     

Flow and heat transfer of a Giesekus fluid in plane and 3D ducts

This study aims to investigate the Graetz problem of Newtonian and viscoelastic fluid obeying Giesekus model using ANSYS Polyflow solver. The non‐isothermal flow in straight ducts of circular and noncircular cross‐sections under the constant heat flux boundary conditions is considered. The effect of the mobility parameter (α), fluid elasticity defined by Weissenberg number (We) and Reynolds number (Re) on the flow field, secondary flows, and the fully developed and developing Nusselt number along the ducts length are investigated for all geometries. The obtained results are of great importance for practical application in the polymer industries such as polymer melt.     

Collaborative Localization for Multi-Robot System with Fault Detection and Exclusion Based on the Kullback-Leibler Divergence

Multi-robot system attracted attention in various applications in order to replace the human operators. To achieve the intended goal, one of the main challenges of this system is to ensure the integrity of localization by adding a sensor fault diagnosis step to the localization task. In this paper, we present a framework able, in addition of localizing a group of robots, to detect and exclude the faulty sensors from the group with an optimized thresholding method. The estimator has the informational form of the Kalman Filter (KF) namely Information Filter (IF). A residual test based on the Kullback-Leibler divergence (KLD) between the predicted and the corrected distributions of the IF is developed. It is generated from two tests: the first acts on the means and the second deals with the covariance matrices. Thresholding using entropy based criterion and Receiver Operating Characteristics (ROC) curve are discussed. Finally, the validation of this framework is studied on real experimental data from a group of robots.     

Combination of Reaction and Separation in Heterogeneous Catalytic Hydrogenation of Ethylformate

Continuous hydrogenation reaction of ethyl benzoylformate was studied over a (–)‐cinchonidine (CD)‐modified Pt/Al₂O₃ catalyst. The catalyst showed a good stability, and high enantioselectivity was achieved in the fixed‐bed reactor. Chromatographic separation of (R)‐ and (S)‐ethyl mandelate originating from a post‐continuous hydrogenation reaction of ethyl benzoylformate over the (–)‐CD‐modified Pt/Al₂O₃ catalyst was investigated in the same reaction mixture. A commercial column filled with a chiral selector resin was chosen as a perspective preparative‐scale adsorbent. Since adsorption equilibrium isotherms were linear within the entire investigated range of concentrations, they were determined by pulse experiments for the isomers present in a post‐reaction mixture. Breakthrough curves were measured and described successfully by the dispersive plug‐flow model with linear driving force approximation.     

Efficient manganese decorated cobalt based catalysts for hydrogenation of 5-hydroxymethylfurfural (HMF) to 2,5-dimethylfuran (DMF) biofuel

2,5-dimethylfuran (DMF) is a promising compound in the production of biofuel with high-quality properties. In this study, it is aimed to develop new efficient catalysts to synthesize DMF from 5-hydroxymethylfurfural (HMF). Co, Mn/Co, and Ru/Co catalysts were prepared using the NaBH₄ reduction method. The catalysts were subjected to activity tests for the hydrogenation of HMF to DMF by changing the reaction parameters, such as temperature and time. Mn/Co catalysts prepared from metal precursors at various molar ratios of Mn/Co were found to be effective in hydrogenation reactions of HMF to DMF. A 91.8% DMF yield was achieved in the presence of a Mn/Co (50/50) catalyst without noble metal at 180°C for 4 hours. The Brunauer-Emmet-Teller (BET) method, x-ray diffraction (XRD), x-ray photoelectron spectroscopy (XPS), and induction coupled plasma mass spectroscopy (ICP-MS) techniques were used to characterize the efficient Mn/Co catalyst.     

Performance improvement of microbial fuel cell through artificial intelligence

The current work introduces an enhancement in the performance of the microbial fuel cell through estimating the optimal set of controlling parameters. The maximization of both power density (PD) and the percentage of chemical oxygen demand (COD) removal were considered as the enhancement in the cell's performance. Three main parameters in terms of performance as well as commercialization are the system's inputs; the Pt which takes the range of 0.1‐0.5 mg/cm², the degree of sulphonation in sulfonated‐poly‐ether‐ether‐ketone that changes in the range of 20‐80%, and the rate of aeration of cathode which varies between 10 and 150 mL/min. From the experimental dataset, two robust adaptive neuro‐fuzzy inference system models based on the fuzzy logic technique have been constructed. The comparisons between the models' outputs and the experimental data showed well‐fitting in both training and testing datasets. The mean squared errors of the PD model, for testing and whole datasets, were found 2.575 and 0.909 while for the COD model it showed 19.242 and 6.791, respectively. Then, based on the two fuzzy models, a Particle Swarm Optimization algorithm has been used to determine the best parameters that maximize both of the PD and the COD removal of the cell. The optimization process was utilized for single and multi‐object optimization processes. In the single optimization, the resulting maximums of the PD and the COD removal were found 62.844 (mW/m²) and 99.99 (%), respectively. Whereas, in the multi‐object optimization, the values of 61.787 (mW/m²) and 96.21 (%) were reached as the maximums for the PD and COD, respectively. This implies that, in both cases of optimization processes, the adopted methodology can efficiently enhance the microbial fuel cell performances than the previous work.     

Efficient Photomodulation of Visible Eu(III) and Invisible Yb(III) Luminescences using DTE Photochromic Ligands for Optical Encryption

This work describes a class of complex combining three dithienylethene units and a lanthanide ion used as an optical system displaying a double encryption method: i) a colorful code, drawn and erased under UV and visible irradiations respectively, due to coloration and discoloration of the photochromic entities, and ii) a concomitant gradual disappearance and progressive restoration of the associated lanthanide ion luminescence triggered with the same stimuli. The innovation of the system stems from the emission color tunability, i.e., with either a lanthanide ion emitting only in the visible range (Eu³⁺) or with another lanthanide ion emitting only in the near infrared (NIR) range (Yb³⁺), therefore observable, or not, to the naked eye. This system is the very first one to achieve efficient repeatable modulation of pure NIR luminescence on photochemical command. Furthermore, it is proven to be highly efficient when embedded in a PDMS polymer opening real opportunities for practical applications as anti‐counterfeiting.     

Exploring network-level performances of wireless nanonetworks utilizing gains of different types of nano-antennas with different materials

Wireless nanonetworks are not a simple extension of traditional communication networks at the nano-scale. Owing to being a completely new communication paradigm, existing research in this field is still at an embryonic stage. Furthermore, most of the existing studies focus on performance enhancement of nanonetworks via designing new channel models and routing protocols. However, the impacts of different types of nano-antennas on the network-level performances of the wireless nanonetworks remain still unexplored in the literature. Therefore, in this paper, we explore the impacts of different well-known types of antennas such as patch, dipole, and loop nano-antennas on the network-level performances of wireless nanonetworks. We also investigate the performances of nanonetworks for different types of traditional materials (e.g., copper) and for nanomaterials (e.g., carbon nanotubes and graphene). We perform rigorous simulation using our customized ns-2 simulation to evaluate the network-level performances of nanonetworks exploiting different types of nano-antennas using different materials. Our evaluation reveals a number of novel findings pertinent to finding an efficient nano-antenna from its several alternatives for enhancing network-level performances of nanonetworks. Our evaluation demonstrates that a dipole nano-antenna using copper material exhibits around 51% better throughput and about 33% better end-to-end delay compared to other alternatives for large-size nanonetworks. Furthermore, our results are expected to exhibit high impacts on the future design of wireless nanonetworks through facilitating the process of finding the suitable type of nano-antenna and suitable material for the nano-antennas.