Physicochemical characterization of low sulfonated polyether ether ketone/Smectite clay composite for proton exchange membrane fuel cells

Polyether ether ketone (PEEK) with a low sulfonation degree was blended using different proportions of sodium rich Smectite clay (3 and 6 wt%) to use as an electrolyte membrane for fuel cell application. The structural functionalities, surface morphologies, and the thermal stability of the resultant composite membranes were characterized using Fourier-transform infrared spectroscopy, X-ray diffraction (XRD), scanning electron microscopy, atom force microscopy, and thermo-gravimetric analysis. FT-IR showed that no chemical reactions take place between the sulfonated polyether ether ketone (SPEEK) and the clay with different ratios. XRD diffractograms illustrated a lower degree of crystallinity of the blended SPEEK than pristine SPEEK. The elaborated composite membranes proved to have a higher thermal stability than SPEEK. Furthermore, the SPEEK/clay composite membranes with 3 and 6 wt% in clay loading had higher water uptake and lower methanol uptake than those in pristine SPEEK It was also shown that, the incorporation of sodium ions rich Smectite clay layers between the clusters in SPEEK improved the conductivity to 2 × 10⁻² S/cm at 140°C (for 6 wt% in clay) without compromising the dimensional stability of the composite membranes. These results propose the composite membranes as a potential candidate for methanol fuel cells at temperatures above 120°C making SPEEK composite membrane competitive to that of Nafion membrane.     

Biodegradable lignin as a reactive raw material in UV curable systems

ABSTRACT

Radiation curing technologies, including ultraviolet (UV) and electron beam curing, have received increasing attention especially after the increasing concerns on energy consumption, environmental protection, and occupational health and safety. Ultraviolet (UV)-curable polymerization are progressively being utilized in numerous manufacturing since they can be speedily applied in addition to their outstanding physical properties such as excellent surface quality, productivity, and slow energy consuming.This paper briefly reviews the research milestones in the area of wood chemical modification, focusing on the basic principles and applications of UV curable systems and polymerization. The study also extends to highlight the effect of lignin incorporation into UV curable system on coating quality, thermal stability, chemical resistance and mechanical properties.     

Optimized Neural Network Prediction Model for Potential Evapotranspiration Utilizing Ensemble Procedure

Potential evapotranspiration (ET_o) is an essential hydrologic parameter for having better understanding for hydrologic cycle in certain catchment area. In addition, ET_o is vital for calculating the agricultural demand. In fact, Penman-Monteith (PM) method is considered as reference method for estimating (ET_o), however, this method required a lot of data to be used which is not usually available in many catchment areas. Furthermore, there are several efforts that have been performed as competitor to reach accurate estimation of (ET_o) when there is lack of data to utilize (PM) method, but still required numerous research. Recently, methods based on Artificial Intelligence (AI) have been suggested to provide reliable prediction model for several application in engineering and especially for hydrological process. However, time series prediction based on Artificial Neural Network (ANN) learning algorithms is fundamentally difficult and faces problem. One of the major shortcomings is that the ANN model experiences over-fitting problem during training session and also occurs when a neural network loses its generalization. In this research a modification for the classical Multi Layer Preceptron- Artificial Neural Network (MLP-ANN) modeling namely; Ensemble Neural Network (ENN) is proposed and applied for predicting daily ET_o. The proposed model applied at two different region with two different climatic conditions, Rasht city located north part of Iran and Johor Bahru City, Johor, Malaysia using maximum and minimum daily temperature collected from 1975 to 2005. The result showed that the ENN outperformed the classical MLP-ANN method and successfully predict daily ETo utilizing maximum and minimum temperature only with satisfactory level of accuracy. In addition, the proposed model could achieve accuracy level better than the traditional competitor methods for ET_o.     

Pro-Apoptotic and Immunotherapeutic Effects of Carbon Nanotubes Functionalized with Recombinant Human Surfactant Protein D on Leukemic Cells

Nanoparticles are efficient drug delivery vehicles for targeting specific organs as well as systemic therapy for a range of diseases, including cancer. However, their interaction with the immune system offers an intriguing challenge. Due to the unique physico-chemical properties, carbon nanotubes (CNTs) are considered as nanocarriers of considerable interest in cancer diagnosis and therapy. CNTs, as a promising nanomaterial, are capable of both detecting as well as delivering drugs or small therapeutic molecules to tumour cells. In this study, we coupled a recombinant fragment of human surfactant protein D (rfhSP-D) with carboxymethyl-cellulose (CMC) CNTs (CMC-CNT, 10–20 nm diameter) for augmenting their apoptotic and immunotherapeutic properties using two leukemic cell lines. The cell viability of AML14.3D10 or K562 cancer cell lines was reduced when cultured with CMC-mwCNT-coupled-rfhSP-D (CNT + rfhSP-D) at 24 h. Increased levels of caspase 3, 7 and cleaved caspase 9 in CNT + rfhSP-D treated AML14.3D10 and K562 cells suggested an involvement of an intrinsic pathway of apoptosis. CNT + rfhSP-D treated leukemic cells also showed higher mRNA expression of p53 and cell cycle inhibitors (p21 and p27). This suggested a likely reduction in cdc2-cyclin B1, causing G2/M cell cycle arrest and p53-dependent apoptosis in AML14.3D10 cells, while p53-independent mechanisms appeared to be in operation in K562 cells. We suggest that CNT + rfhSP-D has therapeutic potential in targeting leukemic cells, irrespective of their p53 status, and thus, it is worth setting up pre-clinical trials in animal models.     

Deep Learning-Based Approach for Arabic Visual Speech Recognition

Lip-reading technologies are rapidly progressing following the breakthrough of deep learning. It plays a vital role in its many applications, such as: human-machine communication practices or security applications. In this paper, we propose to develop an effective lip-reading recognition model for Arabic visual speech recognition by implementing deep learning algorithms. The Arabic visual datasets that have been collected contains 2400 records of Arabic digits and 960 records of Arabic phrases from 24 native speakers. The primary purpose is to provide a high-performance model in terms of enhancing the preprocessing phase. Firstly, we extract keyframes from our dataset. Secondly, we produce a Concatenated Frame Images (CFIs) that represent the utterance sequence in one single image. Finally, the VGG-19 is employed for visual features extraction in our proposed model. We have examined different keyframes: 10, 15, and 20 for comparing two types of approaches in the proposed model: (1) the VGG-19 base model and (2) VGG-19 base model with batch normalization. The results show that the second approach achieves greater accuracy: 94% for digit recognition, 97% for phrase recognition, and 93% for digits and phrases recognition in the test dataset. Therefore, our proposed model is superior to models based on CFIs input.     

Preparation of highly efficient sunlight driven photodegradation of some organic pollutants and H2 evolution over rGO/FeVO4 nanocomposites

FeVO₄ and rGO/FeVO₄ nanocomposites were synthesized by one-step hydrothermal method. The structural and morphological properties of the prepared samples were investigated by XRD, TEM, EDS, XPS, FTIR, Raman, UV–Vis DRS and PL techniques. XRD, XPS and Raman techniques displayed that graphene oxide (GO) was successfully reduced to reduced graphene oxide (rGO) under hydrothermal conditions. Also, the addition of rGO enhanced the visible light absorption, oxygen vacancies, phase transformation of FeVO₄ from triclinic to monoclinic phase at high amount of rGO and reduced the band gap energy of FeVO₄. The photoactivity of the synthesis catalysts was investigated for the photodegradation of Malachite green, phenol, Methylene blue and Rhodamine B under natural sunlight. Also, the catalysts were applied in H₂ evolution from water splitting. The results showed that, the rGO amount was proven to be a crucial factor affecting the structural properties and photocatalytic performance of FeVO₄. The mineralization (TOC), photodegradation mechanism and photocatalytic reaction kinetics were discussed.     

Slipknot or Crystallographic Error: A Computational Analysis of the Plasmodium falciparum DHFR Structural Folds

The presence of protein structures with atypical folds in the Protein Data Bank (PDB) is rare and may result from naturally occurring knots or crystallographic errors. Proper characterisation of such folds is imperative to understanding the basis of naturally existing knots and correcting crystallographic errors. If left uncorrected, such errors can frustrate downstream experiments that depend on the structures containing them. An atypical fold has been identified in P. falciparum dihydrofolate reductase (PfDHFR) between residues 20–51 (loop 1) and residues 191–205 (loop 2). This enzyme is key to drug discovery efforts in the parasite, necessitating a thorough characterisation of these folds. Using multiple sequence alignments (MSA), a unique insert was identified in loop 1 that exacerbates the appearance of the atypical fold-giving it a slipknot-like topology. However, PfDHFR has not been deposited in the knotted proteins database, and processing its structure failed to identify any knots within its folds. The application of protein homology modelling and molecular dynamics simulations on the DHFR domain of P. falciparum and those of two other organisms (E. coli and M. tuberculosis) that were used as molecular replacement templates in solving the PfDHFR structure revealed plausible unentangled or open conformations of these loops. These results will serve as guides for crystallographic experiments to provide further insights into the atypical folds identified.     

The natural gas potential of Saudi Arabia

Kingdom of Saudi Arabia (KSA) has the fourth largest natural gas (NG) reserves in the world. One third of these reserves are located in the Ghawar region of Eastern Province. NG production is controlled tightly due to close conjunction with oil production until recently. KSA’s NG production of 85 billion cubic meters in 2015 from 70 billion cubic meters in 2008 sets an average annual increase of 2.7%. More than half of the annual KSA’s NG production has been accompanied by gas. The Saudi Gas Initiative (SGI) aims to increase foreign investment in the NG development sector through petrochemicals, power generation, and gas development while integrating with salt water desalination. The barriers in the success of motor fuel policies include high initial capital costs, lack of information or skills, less market acceptance, technology limitations, and financing risks. This article aims to review the potential of NG as an alternative to oil and coal in KSA in meeting the country’s high energy requirements.     

Solidification of electrically conducting liquid flow driven by shear and pressure gradients subject to viscous and Joule heating

Solidification of a liquid in motion driven by shear and pressure gradients occurs in many natural settings and technological applications. When the liquid is electrically conducting, its solidification rates can potentially be modulated by an imposed magnetic field. The shearing motion results in viscous dissipation and the Lorentz force induced by the magnetic field causes Joule heating of the fluid, which can influence the structure of the flow, thermal fields, and thereby the solidification process. In this study, a mathematical model is developed to study the combined effects of shear and pressure gradients in the presence of a magnetic field on the solidification of a liquid between two parallel plates, with one of them being insulated and under constant motion, and the other being cooled convectively and at rest. Under the quasi-steady assumption, closed-form semianalytical solutions are obtained for the instantaneous location of the solid–liquid interface, Nusselt number, and dimensionless power density as a function of various characteristic parameters such as the Hartmann number, pressure gradient parameter, Brinkman number, and Biot number. Furthermore, an interesting remelt or steady-state condition for the interfacial location is derived as arising from the competing effects of the solid side heat flux and viscous dissipation and Joule heating on the liquid side. The newly derived analytical results are shown to reduce to the various classical results in the limiting cases. A detailed systematic study is performed by the numerical solution of the semianalytical formulation, and the effects of different characteristic parameters on the solidification process are discussed.