Among the thermoplastic elastomers that play important roles in the polymer industry due to their superior properties, styrene-based species and polyurethane block copolymers are of great interest. Poly(styrene-ethylene-butadiene-styrene) (SEBS) as a triblock copolymer seems to have the potential to meet many demands in different applications due to various industrial requirements where durability, biocompatibility, breaking elongation, and interfacial adhesion are important. In this study, the SEBS triblock copolymer was functionalized with natural (Satureja hortensis, SH) and synthetic (nanopowder, TiO2) agents to obtain composite nanofibers by electrospinning and electrospraying methods for use in biomedical and water filtration applications. The results were compared with thermoplastic polyurethane (TPU) composite nanofibers, which are commonly used in these fields. Here, functionalized SEBS nanofibers exhibited antibacterial effect while at the same time improving cell viability. In addition, because of successful water filtration by using the SEBS composite nanofibers, the material may have a good potential to be used comparably to TPU for the application. 相似文献
The maximization of the total surface area of Pt-SnO2/Al2O3 catalyst was studied by using the Taguchi method of experimental design. The catalysts were prepared by sol-gel method. The
effects of HNO3, H2O and aluminum nitrate concentrations and the stirring rate on the total surface area were studied at three levels of each.
L9 orthogonal array leading nine experiments was used in the experimental design. The parameter levels that give maximum total
surface area were determined and experimentally verified. In the range of conditions studied it was found that, medium levels
of HNO3 and H2O concentration and lower levels of aluminum nitrate concentration and stirring rate maximize the total surface area. 相似文献
In this study, DS5 DK type nanofiltration membranes were tested to recycle the reactive dye bath effluents. Reactive black 5 (RB5), reactive orange 16 (RO16), reactive blue 19 (RB19) and NaCl were used in the experiments to prepare the synthetic dye and salt mixtures. Effects of feed concentration, pressure and cross flow velocity on the permeate flux and color removal were investigated. Permeate flux increased with increasing pressure for all NaCl solutions. Dye concentration had a significant effect on flux values. Under the fixed NaCl concentrations the flux decreased with increasing dye concentrations. Dye rejections greater than 99% were achieved. Permeate was almost colorless. A gel layer formed by the rejected dye on membrane surface operates as a resistance to the permeation of dyes due to complete rejection of high molecule weight dyes, especially for the low salt concentrations. The presence of salt concentration has an interesting effect on color removal. Color removal decreased with increasing salt concentration. Cross flow velocities had also a significant effect on flux values. The dye formed agglomerates at high NaCl concentrations. High cross flow velocities decreased this effect. 相似文献
This study reports a steady-state fluorescence (SSF) technique for studying film formation from surfactant-free polystyrene
(PS) latex and Na-montmorillonite (SNaM) composites. The composite films were prepared from pyrene (P)-labeled PS particles
and SNaM clay at room temperature and annealed at elevated temperatures in 10-min intervals above glass transition temperature
(t3) of polystyrene. During the annealing processes, the transparency of the film improved considerably. Scattered light (Is) and fluorescence intensity (Ip) from P were measured after each annealing step to monitor the stages of film formation. Evolution of transparency of composite
films was monitored by using photon transmission intensity, Itr. Scanning electron microscopy (SEM) was used to detect the variation in physical structure of annealed composite films. Minimum
film formation temperature, Tq, and healing temperatures, Th, were determined. Void closure and interdiffusion stages were modeled and related activation energies were determined. It
was observed that both activation energies increased as the percent of SNaM was increased in composite films. 相似文献
The 2019 novel coronavirus disease (COVID-19), with a starting point in China, has spread rapidly among people living in other countries and is approaching approximately 101,917,147 cases worldwide according to the statistics of World Health Organization. There are a limited number of COVID-19 test kits available in hospitals due to the increasing cases daily. Therefore, it is necessary to implement an automatic detection system as a quick alternative diagnosis option to prevent COVID-19 spreading among people. In this study, five pre-trained convolutional neural network-based models (ResNet50, ResNet101, ResNet152, InceptionV3 and Inception-ResNetV2) have been proposed for the detection of coronavirus pneumonia-infected patient using chest X-ray radiographs. We have implemented three different binary classifications with four classes (COVID-19, normal (healthy), viral pneumonia and bacterial pneumonia) by using five-fold cross-validation. Considering the performance results obtained, it has been seen that the pre-trained ResNet50 model provides the highest classification performance (96.1% accuracy for Dataset-1, 99.5% accuracy for Dataset-2 and 99.7% accuracy for Dataset-3) among other four used models.
In this study, recycled polyethylene (rPE) based microfibrillated composites (MFCs) were developed while incorporating recycled poly(ethylene terephthalate) (rPET) and recycled polyamide 6 (rPA) as the reinforcing fibrillar phases at a given weight ratio of 80 wt% (rPE)/20 wt% (rPET or rPA). The blends were first melt processed using a twin-screw extruder. The extrudates were then cold stretched at a drawing ratio of 2.5 to form rPET and rPA fibrillar structures. Next, the pelletized drawn samples were injection molded at the barrel temperatures below the melting temperatures of rPET and rPA. The tensile, three-point bending, impact strength, dynamic thermomechanical, and rheological properties of the fabricated MFCs were analyzed. The effects of injection molding barrel temperature (i.e., 150°C and 190°C) and extrusion melt processing temperature (i.e., 250°C and 275°C) on the generated fibrillar structure and the resultant properties were explored. A strong correlation between the fibrillar morphology and the mechanical properties with the extrusion and injection molding temperatures was observed. Moreover, the ethylene/n-butyl acrylate/glycidyl methacrylate (EnBAGMA) terpolymer and maleic anhydride grafted PE (MAH-g-PE) were, respectively, melt processed with rPE/rPET and rPE/rPA6 blends as compatibilizers. The compatibilizers refined the fibrillar structure and remarkably influenced mechanical properties, specifically the impact strength. 相似文献
As software systems continue to play an important role in our daily lives, their quality is of paramount importance. Therefore, a plethora of prior research has focused on predicting components of software that are defect-prone. One aspect of this research focuses on predicting software changes that are fix-inducing. Although the prior research on fix-inducing changes has many advantages in terms of highly accurate results, it has one main drawback: It gives the same level of impact to all fix-inducing changes. We argue that treating all fix-inducing changes the same is not ideal, since a small typo in a change is easier to address by a developer than a thread synchronization issue. Therefore, in this paper, we study high impact fix-inducing changes (HIFCs). Since the impact of a change can be measured in different ways, we first propose a measure of impact of the fix-inducing changes, which takes into account the implementation work that needs to be done by developers in later (fixing) changes. Our measure of impact for a fix-inducing change uses the amount of churn, the number of files and the number of subsystems modified by developers during an associated fix of the fix-inducing change. We perform our study using six large open source projects to build specialized models that identify HIFCs, determine the best indicators of HIFCs and examine the benefits of prioritizing HIFCs. Using change factors, we are able to predict 56 % to 77 % of HIFCs with an average false alarm (misclassification) rate of 16 %. We find that the lines of code added, the number of developers who worked on a change, and the number of prior modifications on the files modified during a change are the best indicators of HIFCs. Lastly, we observe that a specialized model for HIFCs can provide inspection effort savings of 4 % over the state-of-the-art models. We believe our results would help practitioners prioritize their efforts towards the most impactful fix-inducing changes and save inspection effort. 相似文献