Improved Interfacial Bonding Strength and Reliability of Functionalized Graphene Oxide for Cement Reinforcement Applications

Poor bonding strength between nanomaterials and cement composites inevitably lead to the failure of reinforcement. Herein, a novel functionalization method for the fabrication of functionalized graphene oxide (FGO), which is capable of forming highly reliable covalent bonds with cement hydration products, and therefore, suitable for use as an efficient reinforcing agent for cement composites, is discussed. The bonding strength between cement and aggregates was improved more than 21 times with the reinforcement of FGO. The fabricated FGO also demonstrated many important features, including high reliability in cement pastes, good dispersibility, and efficient structural refinement of cement hydration products. With the incorporation of FGO, cement mortar samples demonstrated up to 40 % increased early and ultimate strength. Such results make the fast demolding and manufacture of light constructions become highly possible, and show strong advantages on improving productivity, saving cost, and reducing CO₂ emissions in practical applications.     

Optimization of neural network for ionic conductivity of nanocomposite solid polymer electrolyte system (PEO-LiPF6-EC-CNT)

In this study, the ionic conductivity of a nanocomposite polymer electrolyte system (PEO-LiPF₆-EC-CNT), which has been produced using solution cast technique, is obtained using artificial neural networks approach. Several results have been recorded from experiments in preparation for the training and testing of the network. In the experiments, polyethylene oxide (PEO), lithium hexafluorophosphate (LiPF₆), ethylene carbonate (EC) and carbon nanotubes (CNT) are mixed at various ratios to obtain the highest ionic conductivity. The effects of chemical composition and temperature on the ionic conductivity of the polymer electrolyte system are investigated. Electrical tests reveal that the ionic conductivity of the polymer electrolyte system varies with different chemical compositions and temperatures. In neural networks training, different chemical compositions and temperatures are used as inputs and the ionic conductivities of the resultant polymer electrolytes are used as outputs. The experimental data is used to check the system’s accuracy following the training process. The neural network is found to be successful for the prediction of ionic conductivity of nanocomposite polymer electrolyte system.     

Cellular Fucosylation Inhibitors Based on Fluorinated Fucose-1-phosphates**

Fucosylation of glycans impacts a myriad of physiological and pathological processes. Inhibition of fucose expression emerges as a potential therapeutic avenue for example in cancer, inflammation, and infection. In this study, we found that protected 2-fluorofucose 1-phosphate efficiently inhibits cellular fucosylation with a four to seven times higher potency than known inhibitor 2FF, independently of the anomeric stereochemistry. Nucleotide sugar analysis revealed that both the α- and β-GDP-2FF anomers are formed inside the cell. In conclusion, we developed A2FF1P and B2FF1P as potent new tools for studying the role of fucosylation in health and disease and they are potential therapeutic candidates.     

A novel method for serum lipoprotein profiling using high performance capillary isotachophoresis

A new capillary isotachophoresis (cITP) method for lipoprotein profiling with superior lipoprotein coverage compared to previous methods has been developed, resolving twice as many lipoprotein species (18 peaks/fractions) in serum or plasma in less than 9.5 min. For this, a novel mixture of 24 spacers, including amino acids, dipeptides and sulfonic acids, was developed and fine-tuned, using predictive software (PeakMaster) and testing of spiked serum samples. Lipoprotein peaks were identified by serum-spiking with reference lipoproteins. Compatibility with common lipophilic stains for selective lipoprotein detection with either UV/Vis or laser-induced fluorescence was demonstrated. A special new capillary with a neutral coating (combining water-compatible OV1701-OH deactivation and methylation) was used for the first time for electrodriven separations, allowing very stable separations in a pH 8.8–9.4 gradient system, being functional for more than 100 injections. Excellent reproducibility was achieved, with coefficients of variation lower than 2.6% for absolute migration times. Comparison was performed with human plasma samples analyzed by NMR, leading to similar results with cITP after multivariate statistics, regarding group-clustering and lipoprotein species correlation. The new cITP method was applied to the analysis of serum samples from a LDL receptor knock-out mice model fed either a normal diet or a western-type diet. Differences in the lipoprotein levels and in the sublipoprotein types were detected, showing a shift to more atherogenic particles due to the high cholesterol diet. In summary, this novel method will allow more detailed and informative profiling of lipoprotein particle subtypes for cardiovascular disease research.     

Does Euclidean distance work well when the p-median model is applied in rural areas?

The p-median model is used to locate P centers to serve a geographically distributed population. A cornerstone of such a model is the measure of distance between a service center and demand points, i.e. the location of the population (customers, pupils, patients, and so on). Evidence supports the current practice of using Euclidean distance. However, we find that the location of multiple hospitals in a rural region of Sweden with a non-symmetrically distributed population is quite sensitive to distance measure, and somewhat sensitive to spatial aggregation of demand points.     

Interpretation of transport measurements in ZnO-thin films

In order to interpret results of temperature dependent Hall measurements in heteroepitaxial ZnO-thin films, we adopted a multilayer conductivity model considering carrier-transport through the interfacial layer with degenerate electron gas as well as the upper part of ZnO layers with lower conductivity. This model was applied to the temperature dependence of the carrier concentration and mobility measured by Hall effect in a ZnO-layer grown on c-sapphire with conventional high-temperature MgO and low-temperature ZnO buffer. We also compared our results with the results of maximum entropy mobility-spectrum analysis (MEMSA). The formation of the highly conductive interfacial layer was explained by analysis of transmission electron microscopy (TEM) images taken from similar layers.     

Assessment of high-resolution methods for numerical simulations of compressible turbulence with shock waves

Flows in which shock waves and turbulence are present and interact dynamically occur in a wide range of applications, including inertial confinement fusion, supernovae explosion, and scramjet propulsion. Accurate simulations of such problems are challenging because of the contradictory requirements of numerical methods used to simulate turbulence, which must minimize any numerical dissipation that would otherwise overwhelm the small scales, and shock-capturing schemes, which introduce numerical dissipation to stabilize the solution. The objective of the present work is to evaluate the performance of several numerical methods capable of simultaneously handling turbulence and shock waves. A comprehensive range of high-resolution methods (WENO, hybrid WENO/central difference, artificial diffusivity, adaptive characteristic-based filter, and shock fitting) and suite of test cases (Taylor–Green vortex, Shu–Osher problem, shock-vorticity/entropy wave interaction, Noh problem, compressible isotropic turbulence) relevant to problems with shocks and turbulence are considered. The results indicate that the WENO methods provide sharp shock profiles, but overwhelm the physical dissipation. The hybrid method is minimally dissipative and leads to sharp shocks and well-resolved broadband turbulence, but relies on an appropriate shock sensor. Artificial diffusivity methods in which the artificial bulk viscosity is based on the magnitude of the strain-rate tensor resolve vortical structures well but damp dilatational modes in compressible turbulence; dilatation-based artificial bulk viscosity methods significantly improve this behavior. For well-defined shocks, the shock fitting approach yields good results.