Physico‐mechanical properties of nano‐polystyrene‐decorated graphene oxide–epoxy composites

Nano‐polystyrene (nPS)‐decorated graphene oxide (GO) hybrid nanostructures were successfully synthesized using stepwise microemulsion polymerization, and characterized using Fourier transform infrared (FTIR) spectroscopy, X‐ray diffraction (XRD), field‐emission scanning electron microscopy and transmission electron microscopy. XRD and FTIR spectra revealed the existence of a strong interaction between nPS and GO, which implied that the polymer chains were successfully grafted onto the surface of the GO. The nPS‐decorated GO hybrid nanostructures were compounded with epoxy using a hand lay‐up technique, and the effect of the nPS‐decorated GO on the mechanical, thermal and surface morphological properties of the epoxy matrix was investigated using a universal tensile machine, Izod impact tester, thermogravimetric analysis and contact angle measurements with a goniometer. It was observed that in the epoxy matrix, GO improved the compatibility. © 2017 Society of Chemical Industry     

Non-equilibrium solidification of undercooled droplets during atomization process

Thermal history of droplets associated with gas atomization of melt has been investigated. A mathematical model, based on classical theory of heterogeneous nucleation and volume separation of nucleants among droplets size distribution, is described to predict undercooling of droplets. Newtonian heat flow condition coupled with velocity dependent heat transfer coefficient is used to obtain cooling rate before and after nucleation of droplets. The results indicate that temperature profile of droplets in the spray during recalescence, segregated and eutectic solidification regimes is dependent on their size and related undercooling. The interface temperature during solidification of undercooled droplets rapidly approaches the liquidus temperature of the alloy with a subsequent decrease in solid-liquid interface velocity. A comparison in cooling rates of atomized powder particles estimated from secondary dendrite arm spacing measurements are observed to be closer to those predicted from the model during segregated solidification regime of large size droplets.     

Recent Progress on Microfine Design of Metal–Organic Frameworks: Structure Regulation and Gas Sorption and Separation

Metal–organic frameworks (MOFs) have emerged as an important and unique class of functional crystalline hybrid porous materials in the past two decades. Due to their modular structures and adjustable pore system, such distinctive materials have exhibited remarkable prospects in key applications pertaining to adsorption such as gas storage, gas and liquid separations, and trace impurity removal. Evidently, gaining a better understanding of the structure–property relationship offers great potential for the enhancement of a given associated MOF property either by structural adjustments via isoreticular chemistry or by the design and construction of new MOF structures via the practice of reticular chemistry. Correspondingly, the application of isoreticular chemistry paves the way for the microfine design and structure regulation of presented MOFs. Explicitly, the microfine tuning is mainly based on known MOF platforms, focusing on the modification and/or functionalization of a precise part of the MOF structure or pore system, thus providing an effective approach to produce richer pore systems with enhanced performances from a limited number of MOF platforms. Here, the latest progress in this field is highlighted by emphasizing the differences and connections between various methods. Finally, the challenges together with prospects are also discussed.     

Efficient prediction of drug–drug interaction using deep learning models

A drug–drug interaction or drug synergy is extensively utilised for cancer treatment. However, prediction of drug–drug interaction is defined as an ill‐posed problem, because manual testing is only implementable on small group of drugs. Predicting the drug–drug interaction score has been a popular research topic recently. Recently many machine learning models have proposed in the literature to predict the drug–drug interaction score efficiently. However, these models suffer from the over‐fitting issue. Therefore, these models are not so‐effective for predicting the drug–drug interaction score. In this work, an integrated convolutional mixture density recurrent neural network is proposed and implemented. The proposed model integrates convolutional neural networks, recurrent neural networks and mixture density networks. Extensive comparative analysis reveals that the proposed model significantly outperforms the competitive models.Inspec keywords: cancer, learning (artificial intelligence), drugs, recurrent neural nets, convolutional neural nets, drug delivery systemsOther keywords: drug synergy, drug–drug interaction score, drug–drug interaction prediction, deep learning, cancer treatment, machine learning, convolutional mixture density recurrent neural network     

Photosensitization of TiO2 Nanostructures with CdS Quantum Dots: Particulate versus Tubular Support Architectures

TiO₂ nanotube arrays and particulate films are modified with CdS quantum dots with an aim to tune the response of the photoelectrochemical cell in the visible region. The method of successive ionic layer adsorption and reaction facilitates size control of CdS quantum dots. These CdS nanocrystals, upon excitation with visible light, inject electrons into the TiO₂ nanotubes and particles and thus enable their use as photosensitive electrodes. Maximum incident photon to charge carrier efficiency (IPCE) values of 55% and 26% are observed for CdS sensitized TiO₂ nanotube and nanoparticulate architectures respectively. The nearly doubling of IPCE observed with the TiO₂ nanotube architecture is attributed to the increased efficiency of charge separation and transport of electrons.     

Synergistic Use of Pyridine and Selenophene in a Diketopyrrolopyrrole‐Based Conjugated Polymer Enhances the Electron Mobility in Organic Transistors

To achieve semiconducting materials with high electron mobility in organic field‐effect transistors (OFETs), low‐lying energy levels (the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO)) and favorable molecular packing and ordering are two crucial factors. Here, it is reported that the incorporation of pyridine and selenophene into the backbone of a diketopyrrolopyrrole (DPP)‐based copolymer produces a high‐electron‐mobility semiconductor, PDPPy‐Se. Compared with analogous polymers based on other DPP derivatives and selenophene, PDPPy‐Se features a lower LUMO that can decrease the electron transfer barrier for more effective electron injection, and simultaneously a lower HOMO that, however, can increase the hole transfer barrier to suppress the hole injection. Combined with thermal annealing at 240 °C for thin film morphology optimization to achieve large‐scale crystallite domains with tight molecular packing for effective charge transport along the conducting channel, OFET devices fabricated with PDPPy‐Se exhibit an n‐type‐dominant performance with an electron mobility (μ_e) as high as 2.22 cm² V^?1 s^?1 and a hole/electron mobility ratio (μ_h/μ_e) of 0.26. Overall, this study demonstrates a simple yet effective approach to boost the electron mobility in organic transistors by synergistic use of pyridine and selenophene in the backbone of a DPP‐based copolymer.     

On the behavior of thin walled composite beams with stochastic properties under matrix cracking damage

Thin walled composite beam structures are prone to damage which results in change in the performance of these structures. The change in the performance due to damage may get confused with the variation in the performance due uncertainties in the properties of these structures. Here, the performances of the thin walled composite beam under matrix cracking damage having material uncertainties are studied. The cross-sectional stiffness properties are obtained using thin walled beam formulation, which is based on a mixed force and displacement method. The stochastic behaviors of material properties are obtained from previous experimental and analytical studies. The effects of matrix cracking are introduced through the changes in the extension, extension–bending and bending matrices of composites. The effects of matrix cracking on out-of-plane bending, inplane bending and torsion cross-sectional properties are studied at different crack densities for stochastic material properties. Further, the effects of matrix cracking and uncertainties on measurable properties such as deflections and frequencies are studied. Results show that the beam responses at different crack densities get mixed due to the material uncertainties. The estimates of variance obtained for observable system properties due to uncertainty can be used for developing more robust damage detection algorithms.     

Normally Oriented Adhesion versus Friction Forces in Bacterial Adhesion to Polymer‐Brush Functionalized Surfaces Under Fluid Flow

Bacterial adhesion is problematic in many diverse applications. Coatings of hydrophilic polymer chains in a brush configuration reduce bacterial adhesion by orders of magnitude, but not to zero. Here, the mechanism by which polymer‐brush functionalized surfaces reduce bacterial adhesion from a flowing carrier fluid by relating bacterial adhesion with normally oriented adhesion and friction forces on polymer (PEG)‐brush coatings of different softness is studied. Softer brush coatings deform more than rigid ones, which yields extensive bond‐maturation and strong, normally oriented adhesion forces, accompanied by irreversible adhesion of bacteria. On rigid brushes, normally oriented adhesion forces remain small, allowing desorption and accordingly lower numbers of adhering bacteria result. Friction forces, generated by fluid flow and normally oriented adhesion forces, are required to oppose fluid shear forces and cause immobile adhesion. Summarizing, inclusion of friction forces and substratum softness provides a more complete mechanism of bacterial adhesion from flowing carrier fluids than available hitherto.     

LIBS based spectroscopic analysis and antidiabetic evaluation of a polyherbal formulation

Although plants have long been a major source of medicine, there is renewed interest in studying the phytochemistry and use of herbal formulations. This paper reports spectroscopic analysis using Laser Induced Breakdown Spectroscopy (LIBS) of a polyherbal formulation, whose antidiabetic activity has also been demonstrated on rat models. LIBS analysis revealed the presence of elements such as Na, K, Mg, Ca, H, O and N. The antidiabetic study showed that amongst the four doses studied (50, 100, 150 and 200 mg/kg bw), the dose of 150 mg/kg bw registered the maximum fall in Blood Glucose Level (BGL) in both normal and diabetic (sub and mild) rats in the Glucose Tolerance Test (GTT) study—normal rats (22 %), sub-diabetic (36.6 %) and mild-diabetic (39 %). The dose of 150 mg/kg also showed the maximum fall of 23.7 % and 22 % in BGL during fasting BGL and GTT studies of normal rats, respectively. The formulation also showed significant antioxidant activity assessed using in vitro assays. The study validates for the first time the therapeutic use of an antidiabetic polyherbal formulation.     

Synthesis,characterization and comparative OFET behaviour of indenofluorene–bithiophene and terthiophene alternating copolymers

The synthesis of alternating copolymers of tetraalkylindenofluorene with bithiophene and terthiophene using Suzuki polycondensation route is reported. We report on the optical and electrochemical properties of these copolymers. AFM analysis of the microscopic morphology of thin deposits showed that the copolymer with terthiophene units produced the more ordered films, with well-defined fibrillar structures, resulting from highly-regular dense packing due to strong π–π interchain interactions, in contrast to the amorphous bithiophene copolymer. Upon testing these materials in FETs the terthienyl copolymers displayed the higher charge mobilities among the studied compounds, with values of over 10^?4 cm² V^?1 s^?1 being obtained.