Self-assembled fibrillar polyethylene crystals with tunable properties

Due to its simple linear chain structure, crystal morphology of linear low-density polyethylene (LLDPE) fibers can be controlled to fulfill the needs of diverse advanced applications. This study presents a simple two-step method to produce LLDPE fibers with self-assembled fibrillar crystals and highly oriented amorphous phase. Rather than conventional melt spinning, fibers were treated in a two-step eco-friendly bath without drawing after extruded fibers emerge from the spinneret. Treated fibers through the baths demonstrated lower crystallinity, but significantly higher degree of crystal orientation when compared to control fibers of traditional melt spinning. Morphological analysis revealed that a unique microstructure was formed after spinning through a two-step eco-friendly bath. As-spun fibers demonstrated spherulitic morphology which can be transformed into a fibrillar structure followed by post-drawing process. Cross sectional images of the treated LLDPE fibers produced at 400 m/min showed fibrillar PE crystals which can be more dominant upon post-drawing. After two-step bath treatment, produced fibers need low draw ratios to exhibit high performance. Our novel modification followed by hot drawing process can manipulate internal structure with performance of PE fibers to an outstanding level of 0.35 GPa strength and 3 GPa modulus at a production speed of 400 m/min.     

High‐performance filaments by melt spinning low viscosity nylon 6 using horizontal isothermal bath process

Several techniques and treatments have been developed for the production of high‐performance nylon‐6 fibers. The inherent problems of low productivity, high production cost, and high energy consumption, complexity of chemical reaction, mass transfer, and waste recovery systems make most of them inappropriate for industrial application. Horizontal isothermal bath (hIB) is an alternative ecofriendly simple treatment that can be used during melt spinning process for production of technical textile fibers. The efficacy of hIB in improving the mechanical properties of multifilament nylon‐6 yarn is studied in this research. The results showed that such treatment can increase the molecular orientation of the amorphous and crystalline functions up to 0.54 and 0.983, respectively, and raised both the amorphous isotropy and fiber birefringence by 67 and 45%, respectively. Hot drawing of the yarn at a very low draw ratio of 1.38, increased the tenacity and modulus up to 10 and 43.9 g/den, respectively, and decreased the elongation to 27%. POLYM. ENG. SCI., 55:2457–2464, 2015. © 2015 Society of Plastics Engineers     

Synthesis and photopolymerizations of phosphate-containing acrylate/(di)methacrylate monomers from 3-(acryloyloxy)-2-hydroxypropyl methacrylate

Summary Novel phosphorus-containing acrylate/(di)methacrylate monomers based on 3-(acryloyloxy)-2-hydroxypropyl methacrylate (AHM) were prepared by two different methods. The first method involved reaction of AHM with diethylchlorophosphate to produce a phosphate-containing acrylate/methacrylate monomer followed by Michael addition of this monomer with dihexyl amine. In the second method, a hydroxyl-containing dimethacrylate monomer was prepared via Michael addition of hydroxyl amine to AHM followed by its reaction with diethylchlorophosphate. The photopolymerization kinetics of the synthesized monomers were investigated using a differential scanning calorimeter. It was shown that changing the monomer structure allows control of polymerization reactivity and new phosphorus-containing polymers can be obtained.     

Gasification of waste tires in a circulating fixed-bed reactor within the scope of waste to energy

Clean Technologies and Environmental Policy - Thermochemical decomposition of waste tires was evaluated in order to produce solid and gaseous products within the aim of waste-to-energy concept....     

Plastic zones in a transversely isotropic solid cylinder containing a ring–shaped crack

In this study, a problem of a ring shaped-crack contained in a infinitely long solid cylinder of elastic perfectly-plastic material is considered.The problem is formulated for a tranversely isotropic matrial by using integral transform technique under uniform load. Due to the geometry of the configuration, Hankel and Fourier integral transform techniques are chosen and the problem is reduced to a singular integral equation. This integral equation is solved numerically by using Gaussian Quadrature Formulae and the values are evaluated for various for discrete points. The plastic zone widths are obtained by using the plastic strip model. They are plotted for various ring-shaped crack sizes and transversely isotropic matrials. It is found that the width of the plastic zone at the inner tip of the crack is greater than the outer one.     

An expert system based on fuzzy entropy for automatic threshold selection in image processing

In pattern recognition and image processing, the selection of appropriate threshold is a very significant issue. Especially, the selecting gray-level thresholds is a critical issue for many pattern recognition applications. Here, the maximum fuzzy entropy and fuzzy c-partition methods are used for the aim of the gray-level automatic threshold selection method. The fuzzy theory has been successfully applied to many areas, such as image processing, pattern recognition, computer vision, medicine, control, etc. The images have some fuzziness in nature. In this study, expert maximum fuzzy-Sure entropy (EMFSE) method for the maximum fuzzy entropy and fuzzy c-partition processes in automatic threshold selection is proposed. The experimental studies were conducted on many images by testing maximum fuzzy-Sure entropy against maximum fuzzy-Shannon entropy (MFSHE), maximum fuzzy-Havrada and Charvat entropy (MFHCE) methods for selecting optimum 2-level threshold value, respectively. The obtained experimental results show that the used MFSE method is superior to other MFSHE and MFHCE methods on selecting the 2-level threshold value automatically and effectively.     

A new method for expert target recognition system: Genetic wavelet extreme learning machine (GAWELM)

In last year’s, the expert target recognition has been become very important topic in radar literature. In this study, a target recognition system is introduced for expert target recognition (ATR) using radar target echo signals of High Range Resolution (HRR) radars. This study includes a combination of an adaptive feature extraction and classification using optimum wavelet entropy parameter values. The features used in this study are extracted from radar target echo signals. Herein, a genetic wavelet extreme learning machine classifier model (GAWELM) is developed for expert target recognition. The GAWELM composes of three stages. These stages of GAWELM are genetic algorithm, wavelet analysis and extreme learning machine (ELM) classifier. In previous studies of radar target recognition have shown that the learning speed of feedforward networks is in general much slower than required and it has been a major disadvantage. There are two important causes. These are: (1) the slow gradient-based learning algorithms are commonly used to train neural networks, and (2) all the parameters of the networks are fixed iteratively by using such learning algorithms. In this paper, a new learning algorithm named extreme learning machine (ELM) for single-hidden layer feedforward networks (SLFNs) Ahern et al., 1989, Al-Otum and Al-Sowayan, 2011, Avci et al., 2005a, Avci et al., 2005b, Biswal et al., 2009, Frigui et al., in press, Cao et al., 2010, Guo et al., 2011, Famili et al., 1997, Han and Huang, 2006, Huang et al., 2011, Huang et al., 2006, Huang and Siew, 2005, Huang et al., 2009, Jiang et al., 2011, Kubrusly and Levan, 2009, Le et al., 2011, Lhermitte et al., in press, Martínez-Martínez et al., 2011, Matlab, 2011, Nelson et al., 2002, Nejad and Zakeri, 2011, Tabib et al., 2009, Tang et al., 2011, which randomly choose hidden nodes and analytically determines the output weights of SLFNs, to eliminate the these disadvantages of feedforward networks for expert target recognition area. Then, the genetic algorithm (GA) stage is used for obtaining the feature extraction method and finding the optimum wavelet entropy parameter values. Herein, the optimal one of four variant feature extraction methods is obtained by using a genetic algorithm (GA). The four feature extraction methods proposed GAWELM model are discrete wavelet transform (DWT), discrete wavelet transform–short-time Fourier transform (DWT–STFT), discrete wavelet transform–Born–Jordan time–frequency transform (DWT–BJTFT), and discrete wavelet transform–Choi–Williams time–frequency transform (DWT–CWTFT). The discrete wavelet transform stage is performed for optimum feature extraction in the time–frequency domain. The discrete wavelet transform stage includes discrete wavelet transform and calculating of discrete wavelet entropies. The extreme learning machine (ELM) classifier is performed for evaluating the fitness function of the genetic algorithm and classification of radar targets. The performance of the developed GAWELM expert radar target recognition system is examined by using noisy real radar target echo signals. The applications results of the developed GAWELM expert radar target recognition system show that this GAWELM system is effective in rating real radar target echo signals. The correct classification rate of this GAWELM system is about 90% for radar target types used in this study.     

Designing effective professional development for technology integration in schools

This study aims to explore the critical factors for effective professional development (PD) activities to support teachers' technology integration and suggests a design model: flipped PD. The following questions are investigated: What are the core features of effective teacher PD, what are the implications of core features in effective technology integration PD, and what are the best practices for designing a flipped PD model for preparing teachers to integrate technology into their classrooms? First, we discuss the core features of effective teacher PD: content focus, active learning, coherence, duration, collective participation, and the role of context. Second, we explore design factors in recent technology integration PD studies: learner centred, relevance and reflection, evidence of student learning, support and follow-up, student voice, and initial implementation with teacher leaders. Finally, we present a discussion of our recommendations for a flipped model for technology integration PD.