Synthesis and characterization of multiwall carbon nanotube/waterborne polyurethane nanocomposites

The preparation of thermoplastic nanocomposites of waterborne polyurethane (WBPU) and multiwall carbon nanotubes (MWCNTs) via an in situ polymerization approach is presented. The effects of the presence and content of MWCNTs on the morphology and thermal, mechanical and electrical properties of the nanocomposites were investigated. Carbon nanotubes were modified with amide groups in order to enhance their chemical affinity towards WBPU. Thermogravimetric studies show enhanced thermal stability of the nanocomposites. Scanning and transmission electronic microscopy images prove that functionalized carbon nanotubes can be effectively dispersed in WBPU matrix. Mechanical properties reveal that Young's modulus and tensile strength tend to increase when appropriate amounts of MWCNTs are loaded due to the reinforcing effect of the functionalized carbon nanotubes. Thermal properties show an increase in the glass transition temperature and storage modulus with an increase in MWCNT content. X‐ray diffraction reveals better crystallization of the WBPU in the presence of MWCNTs. The WBPU/MWCNT nanocomposite film containing 1 wt% of MWCNTs exhibits a conductivity nearly five orders of magnitude higher than that of WBPU film. © 2017 Society of Chemical Industry     

Physical mechanisms of heat transfer during single bubble nucleate boiling of FC-72 under saturation conditions. II: Theoretical analysis

This paper is the second part of a two-part study concerning the dynamics of heat transfer during the nucleation process of FC-72 liquid. The experimental findings on the nature of different heat transfer mechanisms involved in the nucleation process were discussed in part I. In this paper, the experimental results are compared with the existing boiling models. The boiling models based on dominance of a single mechanism of heat transfer did not match the experimental results. However, the Rohsenow model was found to closely predict the heat transfer through the microconvection mechanism that is primarily active outside the bubble/surface contact area. An existing transient conduction model was modified to predict the surface heat transfer during the rewetting process (i.e. transient conduction mechanism). This model takes into account the gradual rewetting of the surface during the transient conduction process rather than a simple sudden surface coverage assumption commonly used in the boiling literature. The initial superheat energy of the microlayer (i.e. microlayer sensible energy) was accurately calculated and found to significantly contribute in microlayer evaporation. This even exceeded the direct wall heat transfer to microlayer at high surface superheat temperatures. A composite model was introduced that closely matches our experimental results. It incorporates models for three mechanisms of heat transfer including microlayer evaporation, transient conduction, microconvection, as well as their influence area and activation time. The significance of this development is that, for the first time, all submodels of the composite correlation were independently verified using experimental results.     

Curcumin and Liver Disease: from Chemistry to Medicine

Curcumin, the natural yellow‐colored active principle, also called turmeric yellow, extracted from the perennial herb Curcuma longa L., has potent biological and pharmacological properties such as antioxidant, anti‐inflammatory, antifungal, antibacterial, anti‐ischemic, antitumor, and anticancer actions. The molecular mechanism of the hepatoprotective action of curcumin is due to its antioxidant properties and inhibitory activity against nuclear factor (NF)‐κB that regulates different proinflammatory and profibrotic cytokines. Overall, scientific reports demonstrate that curcumin has high therapeutic ability for treating hepatic disorders. Here is a systematic discussion of the hepatoprotective activity of curcumin and its possible mechanisms of actions.     

An analytical investigation of near-field plates

This paper describes an analytical approach to modeling near-field plates, which are non-periodic grating-like structures that can focus electromagnetic waves to subwavelength dimensions. The analysis provides additional insight into the operation and design of such plates that focus cylindrical waves to subwavelength resolutions. Explicit expressions for the current density induced on the plate and its impedance profile are derived. The analytical expressions are validated numerically.     

Decoupled adaptive neuro-fuzzy (DANF) sliding mode control system for a Lorenz chaotic problem

This paper introduces a decoupled adaptive neuro-fuzzy (DANF) sliding mode control system for the chaos control problem in a system without precise system model information. It has on-line learning ability to deal with the parametric uncertainty and disturbance by adjusting the control parameters and no constrained conditions and prior knowledge of the controlled plant is required in the design process. Also, a decoupled adaptive sliding mode controller is developed to control the chaotic Lorenz system for comparison. Finally, the effectiveness of the proposed decoupled adaptive sliding mode and DANF sliding mode controllers are demonstrated by some simulated results.     

Learning gender with support faces

Nonlinear support vector machines (SVMs) are investigated for appearance-based gender classification with low-resolution "thumbnail" faces processed from 1,755 images from the FERET (FacE REcognition Technology) face database. The performance of SVMs (3.4% error) is shown to be superior to traditional pattern classifiers (linear, quadratic, Fisher linear discriminant, nearest-neighbor) as well as more modern techniques, such as radial basis function (RBF) classifiers and large ensemble-RBF networks. Furthermore, the difference in classification performance with low-resolution "thumbnails" (21×12 pixels) and the corresponding higher-resolution images (84×48 pixels) was found to be only 1%, thus demonstrating robustness and stability with respect to scale and the degree of facial detail     

Feature extraction using median–mean and feature line embedding

In this article, we propose a feature extraction method based on median–mean and feature line embedding (MMFLE) for the classification of hyperspectral images. In MMFLE, we maximize the class separability using discriminant analysis. Moreover, we remove the negative effect of outliers on the class mean using the median–mean line (MML) measurement and virtually enlarge the training set using the feature line (FL) distance metric. The experimental results on Indian Pines and University of Pavia data sets show the better performance of MMFLE compared to nearest feature line embedding (NFLE), median–mean line discriminant analysis (MMLDA), and some other feature extraction approaches in terms of classification accuracy using a small training set.     

Performance Evaluation of ANN and ANFIS Models for Estimating Garlic Crop Evapotranspiration

Estimation of evapotranspiration (ET) is necessary in water resources management, farm irrigation scheduling, and environmental assessment. Hence, in practical hydrology, it is often necessary to reliably and consistently estimate evapotranspiration. In this study, two artificial intelligence (AI) techniques, including artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS), were used to compute garlic crop water requirements. Various architectures and input combinations of the models were compared for modeling garlic crop evapotranspiration. A case study in a semiarid region located in Hamedan Province in Iran was conducted with lysimeter measurements and weather daily data, including maximum temperature, minimum temperature, maximum relative humidity, minimum relative humidity, wind speed, and solar radiation during 2008–2009. Both ANN and ANFIS models produced reasonable results. The ANN, with 6-6-1 architecture, presented a superior ability to estimate garlic crop evapotranspiration. The estimates of the ANN and ANFIS models were compared with the garlic crop evapotranspiration (ETc) values measured by lysimeter and those of the crop coefficient approach. Based on these comparisons, it can be concluded that the ANN and ANFIS techniques are suitable for simulation of ETc.     

LaMer diagram approach to study the nucleation and growth of Cu2O nanoparticles using supersaturation theory

Uptake to cuprous oxide (Cu₂O) nanoparticle synthesis with various particle sizes and shapes via supersaturation chemistry approach (LaMer model) has been conducted. Ascorbic acid and maltodextrine as reducing agents and polyvinylpyrrolidone (PVP) as a surfactant were utilized for synthesis of Cu₂O nanoparticles in aqueous solution. The narrow particle size range was achieved by controlling the kinetics of nucleation and growth of particles to satisfy LaMer theory. This mean was performed utilizing different reducing agents (ascorbic acid and maltodextrin) and also, changing the reducing agent addition condition. The results showed the reducing agent addition condition, varying the size of Cu₂O nanoparticles from 89 nm to 74 nm for drop-wisely and at-once routes, respectively. The samples were characterized by XRD, SEM, and UV-Vis spectroscopy. The results indicate the shape of as-prepared cuprous oxide nanoparticles have close relationship with thermodynamic and kinetic conditions, and also reducing addition condition.     

Multifunctional Gadolinium‐Doped Mesoporous TiO2 Nanobeads: Photoluminescence,Enhanced Spin Relaxation,and Reactive Oxygen Species Photogeneration,Beneficial for Cancer Diagnosis and Treatment

Materials with controllable multifunctional abilities for optical imaging (OI) and magnetic resonant imaging (MRI) that also can be used in photodynamic therapy are very interesting for future applications. Mesoporous TiO₂ sub‐micrometer particles are doped with gadolinium to improve photoluminescence functionality and spin relaxation for MRI, with the added benefit of enhanced generation of reactive oxygen species (ROS). The Gd‐doped TiO₂ exhibits red emission at 637 nm that is beneficial for OI and significantly improves MRI relaxation times, with a beneficial decrease in spin–lattice and spin–spin relaxation times. Density functional theory calculations show that Gd³⁺ ions introduce impurity energy levels inside the bandgap of anatase TiO₂, and also create dipoles that are beneficial for charge separation and decreased electron–hole recombination in the doped lattice. The Gd‐doped TiO₂ nanobeads (NBs) show enhanced ability for ROS monitored via ^?OH radical photogeneration, in comparison with undoped TiO₂ nanobeads and TiO₂ P25, for Gd‐doping up to 10%. Cellular internalization and biocompatibility of TiO₂@x Gd NBs are tested in vitro on MG‐63 human osteosarcoma cells, showing full biocompatibility. After photoactivation of the particles, anticancer trace by means of ROS photogeneration is observed just after 3 min irradiation.