Effects of carbon nanotubes and interphase properties on the interfacial conductivity and electrical conductivity of polymer nanocomposites

L_c is the minimum length of carbon nanotubes (CNTs) required for efficient transfer of filler conductivity to polymer matrix in polymer CNT nanocomposites (PCNTs). In this work, L_c is correlated with the dimensions of the CNTs and the interphase thickness. Subsequently, the interfacial conductivity as well as the effective length and concentration of CNTs are expressed by CNT and interphase properties. Moreover, a simple model for the tunneling conductivity of PCNTs is developed with these effective terms. The impacts of all parameters on L_c, the interfacial conductivity, the fraction of CNTs in the networks and the conductivity of the PCNT are explained and justified. In addition, the predictions of the percolation threshold and conductivity are compared with the experimental results of several samples. The desirable values of interfacial conductivity are achieved by thin, short and super‐conductive CNTs, high waviness and a thick interphase. However, thin and long CNTs, low waviness, a thick interphase, poor tunneling resistivity due to the polymer matrix and a short tunneling distance advantageously affect the conductivity of PCNTs, because they produce large conductive networks. The predictions also show good agreement with the experimental measurements of percolation threshold and conductivity, which confirms the developed equations. © 2020 Society of Chemical Industry     

Photo-crosslinking: An Emerging Chemical Tool for Investigating Molecular Networks in Live Cells

Studying protein–protein interactions (PPIs) is useful for understanding cellular functions and mechanisms. Evaluating these PPIs under conditions as similar as possible to native conditions can be achieved using photo-crosslinking methods because of their on-demand ability to generate reactive species in situ by irradiation with UV light. Various fusion tag, metabolic incorporation, and amber codon suppression approaches using various crosslinkers containing aryl azide, benzophenone, and diazirines have been applied in live cells. Mass spectrometry and immunological techniques are used to identify crosslinked proteins based on their capture transient and context-dependent interactions. Herein we discuss various incorporation methods and crosslinkers that have been used for interactome mapping in live cells.     

Effect of propolis phenolic compounds on free fatty acid receptor 4 activation

Food Science and Biotechnology - Propolis is known to have multiple biological and pharmacological properties including the regulation of energy homeostasis. Although phenolic compounds are...     

In vivo Kinetic Biodistribution of Nano‐Sized Outer Membrane Vesicles Derived from Bacteria

Evaluation of kinetic distribution and behaviors of nanoparticles in vivo provides crucial clues into their roles in living organisms. Extracellular vesicles are evolutionary conserved nanoparticles, known to play important biological functions in intercellular, inter‐species, and inter‐kingdom communication. In this study, the first kinetic analysis of the biodistribution of outer membrane vesicles (OMVs)—bacterial extracellular vesicles—with immune‐modulatory functions is performed. OMVs, injected intraperitoneally, spread to the whole mouse body and accumulate in the liver, lung, spleen, and kidney within 3 h of administration. As an early systemic inflammation response, increased levels of TNF‐α and IL‐6 are observed in serum and bronchoalveolar lavage fluid. In addition, the number of leukocytes and platelets in the blood is decreased. OMVs and cytokine concentrations, as well as body temperature are gradually decreased 6 h after OMV injection, in concomitance with the formation of eye exudates, and of an increase in ICAM‐1 levels in the lung. Following OMV elimination, most of the inflammatory signs are reverted, 12 h post‐injection. However, leukocytes in bronchoalveolar lavage fluid are increased as a late reaction. Taken together, these results suggest that OMVs are effective mediators of long distance communication in vivo.     

Assessing the aggregation behaviour of iron oxide nanoparticles under relevant environmental conditions using a multi-method approach

Iron nanoparticles are becoming increasingly popular for the treatment of contaminated soil and groundwater; however, their mobility and reactivity in subsurface environments are significantly affected by their tendency to aggregate. Assessing their stability under environmental conditions is crucial for determining their environmental fate. A multi-method approach (including different size-measurement techniques and the DLVO theory) was used to thoroughly characterise the behaviour of iron oxide nanoparticles (Fe₂O₃NPs) under environmentally relevant conditions. Although recent studies have demonstrated the importance of using a multi-method approach when characterising nanoparticles, the majority of current studies continue to use a single-method approach.Under some soil conditions (i.e. pH 7, 10 mM NaCl and 2 mM CaCl₂) and increasing particle concentration, Fe₂O₃NPs underwent extensive aggregation to form large aggregates (>1 μm). Coating the nanoparticles with dissolved organic matter (DOM) was investigated as an alternative “green” solution to overcoming the aggregation issue instead of using the more commonly proposed polyelectrolytes. At high concentrations, DOM effectively covered the surface of the Fe₂O₃NPs, thereby conferring negative surface charge on the particles across a wide range of pH values. This provided electrostatic stabilisation and considerably reduced the particle aggregation effect. DOM-coated Fe₂O₃NPs also proved to be more stable under high ionic strength conditions. The presence of CaCl₂, however, even at low concentrations, induced the aggregation of DOM-coated Fe₂O₃NPs, mainly via charge neutralisation and bridging. This has significant implications in regards to the reactivity and fate of these materials in the environment.     

Effect of grain size and density of spray-pyrolyzed hydroxyapatite particles on the sinterability of hydroxyapatite disk

The effect of grain size and density of hydroxyapatite particles, which were prepared by different spray-pyrolysis temperatures, on the sinterability of hydroxyapatite disk was investigated. Calcium phosphate solution (Ca/P ratio of 1.67 and 0.1 M concentration) was prepared by reacting calcium nitrate tetrahydrate and diammonium hydrogen phosphate solutions, and adding nitric acid. Spray-pyrolysis was carried out at 900 °C, 1200 °C, and 1500 °C at a carrier gas flowing rate of 10 L/min. The particles synthesized at 900 °C were large, hollow spheres with a hole at the outer surface, a broad size distribution, but had small grain sizes. Conversely, the particles synthesized at 1500 °C were small, solid spheres with a narrow size distribution, but had large grain sizes. The particles synthesized at 1200 °C had intermediate properties. A sinterability test conducted at 1100 °C for 1 h demonstrated that small and dense particles with large grain sizes showed a higher relative sintered density compared with large and hollow particles with small grain sizes. The results were explained in terms of the grain size and density of a particle, which were inversely and proportionally affected to sinterability. The practical implication of these results is that highly sinterable hydroxyapatite powders can be synthesized through spray-pyrolysis at a high temperature under a fixed initial concentration of calcium phosphate solution and flow rate of carrier gas.     

Modelling and optimization of a GMA welding process by genetic algorithm and response surface methodology

The welding process, due to its complexity, has relied on empirical and experimental data to determine its welding conditions. However, trial-and-error methods to determine optimal conditions incur considerable time and cost. In order to overcome these problems, a genetic algorithm and response surface methodology have been suggested for determining optimal welding conditions. First, in a relatively broad region, near-optimal conditions were determined through a genetic algorithm. Then, the optimal conditions for welding were determined over a relatively small region around these near-optimal conditions by using response surface methodology. In order to give different objective function values according to the positive or negative response from the set target value in the optimization problem, a desirability function approach was used. Application of the method proposed in this paper revealed a good result for finding the optimal welding conditions in the gas metal arc (GMA) welding process.     

Optimization of GMA welding process using the dual response approach

Disturbances and changes in the welding working environment lead to possible variations in the output variables associated with weld quality. In order to enhance weld quality, it is essential to optimize the welding process by taking the variance as well as the average value of the output variables into consideration. In this study, the dual response approach is adopted to determine the welding process parameters, which produce the target value with minimal variance. The dual response approach optimizes the penetration in gas metal arc (GMA) welding through the procedures as follows. First, the regression models of the mean value and standard deviation of the penetration are induced through regression analysis. Subsequently, an optimization algorithm based on the regression models and constraints is applied to determine the welding process parameters, which generate the desired penetration with minimized variance. In particular, the genetic algorithm, a global optimization algorithm, is adopted in this study to determine the optimal solution.