Synthesis, characterization and properties of novel thermally stable poly(urethane-oxazolidone) elastomers

Oxazolidone-incorporated polyurethane elastomers based on hydroxyl terminated polycaprolactone, were synthesized and characterized. Reaction of epoxy-terminated polyurethane with isocyanate librated from a blocked polyisocyanate was the strategy followed. The reaction condition was optimized through preparation of model oxazolidones. Epoxy-terminated polyurethanes were prepared from reaction of glycidol with NCO-terminated polyurethane prepolymers and curing agent was synthesized from the reaction of trimethylol propane, toluene diisocyanate and N-methyl-aniline. Incorporation of heterocyclic oxazolidone groups into the polyurethane backbone caused improvements in thermal and mechanical properties. Investigation of structure-property relationship for prepared elastomers showed that the main determining factors for observed properties were crosslink density, crystallinity and content of oxazolidone rings.     

Rapid Learning-Based and Geologically Consistent History Matching

Various types of data become available at different stages of a reservoir’s life. The production data are integrated into the flow simulation models through a process referred to as history matching. The history-matching process is iterative, and it usually involves a large number of simulation runs. Hence, this process requires significant computational time. In most history-matching methods, the initial geological assumptions in the reservoir model are destroyed or significantly altered in the process. Furthermore, they do not account for the information obtained during the previous trials, and lack learning from the previous failures. In this paper, we introduce a new methodology that maintains the geological realism. The candidate realizations are selected through a learning-based history-matching (LHM) algorithm by which all the previously successful patterns are preserved and used to assist the construction of the next realizations. The various pieces of matching regions are assembled together to make a pool of the successful candidates. Such regions are then utilized for making an auxiliary dataset in a multiscale framework by which the next model is generated. To prevent from trapping in local minima, ideas from the genetic algorithm is adapted. The LHM algorithm can be applied to both categorical and continuous distributions. The LHM provides a conditional map by which the new production data are immediately incorporated into the existing reservoir models. We apply the LHM algorithm to various 2D and 3D examples with very complex binary and continuous properties. The algorithm is shown to produce history-matched models with significantly smaller CPU times.     

Exploring the origin of tip‐enhanced Raman scattering; preparation of efficient TERS probes with high yield

Tip‐enhanced Raman scattering (TERS) spectroscopy is a promising technique for nanoscale chemical analysis. However, there are several challenges preventing widespread application of this technology, including reproducible fabrication of efficient TERS probes. These problems reflect a lack of clear understanding of the origins of, and the parameters influencing TERS. It is believed that the coating characteristics at the apex of the tip have a major effect on the near‐field optical enhancement and thus the TERS activity of a metalized probe. Here we show that the aspect ratio of the tip can play a significant role in the efficiency of TERS probes. We argue that the electrostatic field arising from the lightning‐rod effect has a substantial role in the observed TERS effect. This argument is supported by ‘edge‐enhanced Raman scattering’ which is shown for a noble metal film. Furthermore, it is reported that an associated tip‐surface‐enhanced Raman scattering effect can be achieved by using a TERS‐inactive metalized probe on a surface‐enhanced Raman spectroscopy‐inactive roughened surface. This observation can be explained by an interparticle enhancement of the electromagnetic field. Copyright © 2011 John Wiley & Sons, Ltd.     

Direct Synthesis of PbO Nanoparticles From a Lead(II) Nano Coordination Polymer Precursor: Synthesis,Crystal Structure,and DFT Calculations of [Pb2(dmp)2(μ‐N3)2(μ‐ClO4)2]n with the First Pb2‐(μ‐ClO4)2 Unit

Nanostructures of a new coordination polymer of divalent lead with the ligand 2, 9‐dimethyl‐1, 10‐phenanthroline (dmp) containing the first Pb₂‐(μ‐ClO₄)₂ motif, [Pb₂(dmp)₂(μ‐N₃)₂(μ‐ClO₄)₂]_n ( 1 ), was synthesized by a sonochemical method that produces the coordination polymers at nano size. The new nanostructure was characterized by scanning electron microscopy, X‐ray powder diffraction, IR, ¹H NMR and ¹³C NMR spectroscopy, and elemental analysis. Compound 1 was structurally characterized by single‐crystal X‐ray diffraction and the single‐crystal X‐ray data shows that the coordination number of Pb^II ions is six, (PbN₄O₂), with two N‐donor atoms from aza‐aromatic base ligands and four O‐donors from two perchlorate anions and two N‐donors from two azide anions. It has a “stereo‐chemically active” electron lone pair, and the coordination sphere is hemidirected. The supramolecular features in these complexes are guided and controlled by weak directional intermolecular interactions. The chains interact with each other through π–π stacking interactions creating a 3D framework. The structure of the title complex was optimized by density functional theory calculations. Calculated structural parameters and IR spectra for the title complex are in agreement with the crystal structure. The PbO nanoparticles were obtained by thermolysis of 1 at 180 °C with oleic acid as a surfactant. The average diameter of the nanoparticles was estimated by the Scherrer equation to be 23 nm. The morphology and size of the prepared PbO samples were further observed using SEM.     

Characterization of biochemical traits of dog rose (Rosa canina L.) ecotypes in the central part of Iran

Dog rose (Rosa canina L.) is a wild native species in Iran, with a significant genetic diversity. This plant serves as a rich source of vitamin C, anthocyanins, phenolic contents and carotenoids. Rose hips have been used in several food products, as well as perfumery and cosmetics industries. In this research, we investigate biochemical characteristics of five dog rose ecotypes (Kopehjamshid, Zarneh, Miyankish, Aghcheh and Sadeghiyeh), that were collected from the central part of Iran (Isfahan province). Amounts of vitamin C, total carotenoids, total phenolic contents, total anthocyanins, macro and micro minerals were measured. Seed oil are extracted by soxhlet method and analysed by gas chromatography. The macro and micro minerals levels in the fruit vary significantly among these regions. The results of this study demonstrate that dog rose have great diversity and can be used in breeding programmes in order to increase nutrient values as a food resource additive.     

Fuzzy chance-constrained data envelopment analysis: a structured literature review,current trends,and future directions

Fuzzy Optimization and Decision Making - Fuzzy data envelopment analysis (FDEA) is one of the most applicable approaches for performance assessment of peer decision making units under ambiguity...     

Linking Morphology of Porous Media to Their Macroscopic Permeability by Deep Learning

Flow, transport, mechanical, and fracture properties of porous media depend on their morphology and are usually estimated by experimental and/or computational methods. The precision of the computational approaches depends on the accuracy of the model that represents the morphology. If high accuracy is required, the computations and even experiments can be quite time-consuming. At the same time, linking the morphology directly to the permeability, as well as other important flow and transport properties, has been a long-standing problem. In this paper, we develop a new network that utilizes a deep learning (DL) algorithm to link the morphology of porous media to their permeability. The network is neither a purely traditional artificial neural network (ANN), nor is it a purely DL algorithm, but, rather, it is a hybrid of both. The input data include three-dimensional images of sandstones, hundreds of their stochastic realizations generated by a reconstruction method, and synthetic unconsolidated porous media produced by a Boolean method. To develop the network, we first extract important features of the images using a DL algorithm and then feed them to an ANN to estimate the permeabilities. We demonstrate that the network is successfully trained, such that it can develop accurate correlations between the morphology of porous media and their effective permeability. The high accuracy of the network is demonstrated by its predictions for the permeability of a variety of porous media.

     

A theoretical practice on grazing‐exit energy dispersive X‐ray spectroscopy as a surface analysis strategy to investigate BiVO4 nano‐films

In the current work, a thin film of bismuth vanadate was defined over a silicon substrate, and a calculative Monte Carlo approach was followed to achieve the best grazing‐exit angle to acquire compositional data from top few nanometers of surface. This strategy is very beneficial in order to increase X‐ray signals originated from surface and diminish the background X‐ray signals started off from the substrate. In this regard, grazing‐exit energy dispersive X‐ray spectroscopy can be considered as an accessible and economical analytical tool to investigate thin films and nano‐layers. The major advantage of this method is that just by applying a re‐arrangement in a scanning electron microscope, it can be used to study compositional properties of thin layers. In this contribution, a theoretical approach using Monte Carlo models was used to simulate the behavior of electron beams impinging onto BiVO₄ nano‐layers with thickness of 50 nm and electron trajectories inside the film. Characteristic X‐rays and spatial energy distribution of the backscattered electrons were also calculated. Under grazing‐exit angle of around 0.5°, the best surface signal/background noise ratio was achieved. Copyright © 2014 John Wiley & Sons, Ltd.     

Investigation of cross-linked PVA/starch biocomposites reinforced by cellulose nanofibrils isolated from aspen wood sawdust

In this study, a bio-based composite prepared from cross-linked polyvinyl alcohol/starch/cellulose nanofibril (CNF) was developed for film packaging applications. For this purpose, CNF, as reinforcing phase, was initially isolated from aspen wood sawdust (AWS) using chemo-mechanical treatments, and during these treatments, hydrolysis conditions were optimized by experimental design. Morphological and chemical characterizations of AWS fibers were studied by transmission electron microscopy, scanning electron microscopy, Kappa number, and attenuated total reflectance-Fourier transform infrared spectroscopy, as well as National Renewable Energy Laboratory and ASTM procedures. Morphological images showed that the diameter of the AWS fibers was dramatically decreased during the chemo-mechanical treatments, proving the successful isolation of CNF. Moreover, chemical composition results indicated the successful isolation of cellulose, and Kappa number analysis demonstrated a dramatic reduction in lignin content. Mechanical, morphological, biodegradability, and barrier properties of biocomposites were also investigated to find out the influence of CNF on the prepared biocomposite properties. The mechanical results obtained from tensile analysis revealed that Young’s modulus and ultimate tensile strength of biocomposite films were enhanced with increasing CNF concentration, while a significant decrease was observed in elongation at break at the same concentration of CNF. Furthermore, with adding CNF, barrier properties and resistance to biodegradability were increased in films, whereas film transparency gradually declined.     

Effect of different microwave-based treatments on multi-walled carbon nanotubes

Three new methods for the functionalization of multi-walled carbon nanotubes (MWCNTs) are reported using microwave (MW) energy and water as a mild chemical agent. In the first method we reported the effect of MW irradiation on a dispersion of MWCNTs in deionized water, in the second method we studied the exposing of MWCNT to microwave irradiation in the presence of steam, and in the third method we used microwave oven-generated plasma for the functionalization of MWCNTs. We also performed thermal oxidation and acid treatment as two conventional methods for oxidative functionalization of carbon nanotubes, to compare their effect with our results. Transmission electron microscopy (TEM) and Raman spectroscopy results showed that although these microwave methods introduced some defects to the carbon nanotubes, the damage was less severe than conventional treatments. X-ray photoelectron spectroscopy (XPS) measurements confirmed that the functionalization of carbon nanotubes by these methods favored hydroxyl groups, which are useful when further functionalization is required.