Growth mechanisms of MgO nanocrystals via a sol-gel synthesis using different complexing agents

In the preparation of nanostructured materials, it is important to optimize synthesis parameters in order to obtain the desired material. This work investigates the role of complexing agents, oxalic acid and tartaric acid, in the production of MgO nanocrystals. Results from simultaneous thermogravimetric analysis (STA) show that the two different synthesis routes yield precursors with different thermal profiles. It is found that the thermal profiles of the precursors can reveal the effects of crystal growth during thermal annealing. X-ray diffraction confirms that the final products are pure, single phase and of cubic shape. It is also found that complexing agents can affect the rate of crystal growth. The structures of the oxalic acid and tartaric acid as well as the complexation sites play very important roles in the formation of the nanocrystals. The complexing agents influence the rate of growth which affects the final crystallite size of the materials. Surprisingly, it is also found that oxalic acid and tartaric acid act as surfactants inhibiting crystal growth even at a high temperature of 950°C and a long annealing time of 36 h. The crystallite formation routes are proposed to be via linear and branched polymer networks due to the different structures of the complexing agents.     

Fault-tolerant communications for wafer-scale integration of a processor array

This paper describes schemes for introducing fault-tolerance into a two-dimensional orthogonal array of cells with nearest neighbour communication paths. The schemes are designed to tolerate a large number of faults and are therefore applicable to the yield-enhancement of large-area VLSI circuits. Simulation results are presented which show the superiority of the schemes over previous proposals and indicate that the nearest neighbour interconnections need not be a barrier to the desirable goal of integrating an array computer onto a whole-wafer circuit.     

Fuzzy-based sustainability evaluation method for manufacturing SMEs using balanced scorecard framework

Sustainability has become a necessity, partly due to the threats created by traditional manufacturing practices, and due to regulations imposed by stakeholders. Performance evaluation is an important component of sustainability initiatives in manufacturing organizations. This study proposes a sustainability evaluation method for manufacturing SMEs using integrated fuzzy analytical hierarchal process (FAHP) and fuzzy inference system (FIS) approach. The performance indicators are identified from literature considering the characteristics of SMEs. Balanced scorecard framework is used to categorize the indicators among its four aspects. The linguistic variables are used to collect the opinions of decision makers about the performance ratings and importance of the aspects and corresponding indicators. The FAHP method is applied to determine the relative weights of measures and indicators. The performance ratings of the organization with respect to indicators and relative weights of indicators are combined to obtain the weighted performance ratings. The weighted performance ratings are considered as inputs to FIS. The hierarchal FIS is applied to derive the overall sustainability performance. Using a case study of manufacturing SME, the sustainability score of the organization was elicited in accordance with this procedure. Consequently, a sensitivity analysis of the proposed method reveals the most important basic indicators affecting overall sustainability, identifying areas which decision makers should place special attention. This method can also assist managers of larger enterprises to assess the effectiveness of their sustainability strategies, especially when dealing with suppliers from the SMEs.     

Modular and Versatile Spatial Functionalization of Tissue Engineering Scaffolds through Fiber‐Initiated Controlled Radical Polymerization

Native tissues are typically heterogeneous and hierarchically organized, and generating scaffolds that can mimic these properties is critical for tissue engineering applications. By uniquely combining controlled radical polymerization (CRP), end‐functionalization of polymers, and advanced electrospinning techniques, a modular and versatile approach is introduced to generate scaffolds with spatially organized functionality. Poly‐ε‐caprolactone is end functionalized with either a polymerization‐initiating group or a cell‐binding peptide motif cyclic Arg‐Gly‐Asp‐Ser (cRGDS), and are each sequentially electrospun to produce zonally discrete bilayers within a continuous fiber scaffold. The polymerization‐initiating group is then used to graft an antifouling polymer bottlebrush based on poly(ethylene glycol) from the fiber surface using CRP exclusively within one bilayer of the scaffold. The ability to include additional multifunctionality during CRP is showcased by integrating a biotinylated monomer unit into the polymerization step allowing postmodification of the scaffold with streptavidin‐coupled moieties. These combined processing techniques result in an effective bilayered and dual‐functionality scaffold with a cell‐adhesive surface and an opposing antifouling non‐cell‐adhesive surface in zonally specific regions across the thickness of the scaffold, demonstrated through fluorescent labelling and cell adhesion studies. This modular and versatile approach combines strategies to produce scaffolds with tailorable properties for many applications in tissue engineering and regenerative medicine.     

A simple pharmacokinetic model of alendronate developed using plasma concentration and urine excretion data from healthy men

The study of pharmacokinetics of alendronate has been hampered by difficulties in accurately and reproducibly determining their concentrations in serum and urine. Thus, pharmacokinetic characteristics of alendronate have been described in many reports based on urinary excretion data; and plasma pharmacokinetics and the simultaneous pharmacokinetic models of alendronate in plasma and urine are not available. The aims of this study were to measure alendronate concentration in plasma and excretion in urine concurrently and to develop compartmental pharmacokinetic model using urine data. In open-label, single-dose pharmacokinetic study, 10 healthy male volunteers received oral dose of alendronate (70?mg tablet). Blood and urine alendronate concentrations were determined using validated high-performance liquid chromatography method. Non-compartmental analysis was performed using WinNonlin program (Pharsight Inc., Apex, NC). A one-compartment pharmacokinetic model was applied to describe pharmacokinetics of alendronate. A peak plasma alendronate concentration of 33.10?±?14.32?ng/mL was attained after 1.00?±?0.16?h. The cumulative amount of alendronate excreted in urine and peak excretion rate were 731.28?±?654.57?μg and 314.68?±?395.43?μg/h, respectively. The model, which included first-order absorption rate for oral dosing, showed good fit to alendronate data obtained from plasma and urine. The absorption rate constant was 2.68?±?0.95?h^–1. The elimination rate constants K_urine and K_non-ur were 0.005?±?0.004?h^?1 and 0.42?±?0.08?h^?1, respectively. The pharmacokinetics of alendronate in plasma and urine of healthy men can be predicted using one-compartment model, and thus the behavior of drug in plasma can be estimated from urinary excretion data.     

Control and operation of distributed generation in distribution systems

Many distribution systems nowadays have significant penetration of distributed generation (DG) and thus, islanding operation of these distribution systems is becoming a viable option for economical and technical reasons. The DG should operate optimally during both grid-connected and island conditions, which can be achieved with change in operating strategy. Many islanding detection techniques have been developed but little work has been done to detect grid re-connection. This paper presents strategies to operate DG in grid connected and islanded modes and a new grid re-connection detection algorithm, which uses average rate of change of frequency (Af5) and real power shift (RPS), in the islanded mode. RPS will increase or decrease the power set point of the generator with increasing or decreasing system frequency, respectively. Simulation results show that the proposed method can operate the DG efficiently and is effective in detecting grid-reconnection.     

Development of al-doped MgMn2O4-based cathode materials for magnesium ion cells

Magnesium ion battery is an alternative for secondary battery instead of lithium ion battery due to its advantages of low cost, safety and environment friendly. Magnesium (Mg) is safer compared to lithium (Li) where it has high stability in contact of air and prevent the formation of dendrites during electrochemical cycling. The cathode materials of un-doped MgMn₂O₄ and Al-doped MgMn_2-xAl_xO₄, x = .01, .02, .03 were prepared using self-propagating combustion method with triethanolamine fuel as a reducing agent. All samples (powder form) were annealed at 700˚C in 6 h based on the thermogravimetric analysis results. The samples were been characterized using X ray diffraction, field emission electron microscopy, energy-dispersive X-ray spectroscopy and high-resolution transmission electron microscopy to study structural and morphological properties of the samples. Electrochemical properties of linear sweep voltammetry, cyclic voltammetry, and charge-discharge capacity were performed in 1 M Magnesium Trifluoromethanesulfonate (MgTf₂) with ratio 1:1 of ethylene carbonate: dimethyl ether electrolyte. The discharge capacity of magnesium ion cells using Al-doped cathode material showed the improvement of 68% compared to the un-doped sample.     

Effects of Positive Carbon Quantum Dots on Gram-Negative Bacteria as an Antimicrobial Agent

Journal of Inorganic and Organometallic Polymers and Materials - Non-radiative decay is the main limitation to applications of the excellent optical properties of carbon quantum dots. Moreover, the...     

An analytical approach for DG allocation in primary distribution network

This paper proposes an analytical expression to calculate the optimal size and an effective methodology to identify the corresponding optimum location for DG placement for minimizing the total power losses in primary distribution systems. The analytical expression and the methodology are based on the exact loss formula. The effect of size and location of DG with respect to loss in the network is also examined in detail. The proposed methodology was tested and validated in three distribution test systems with varying size and complexity. Results obtained from the proposed methodology are compared with that of the exhaustive load flows and loss sensitivity method. Results show that the loss sensitivity factor based approach may not lead to the best placement for loss reduction.