Performance comparison of modified poly(vinyl alcohol) based membranes in alkaline fuel cells

There are several problems which are holding back the use of fuel cells. The utilization of fuel cells depends on the start-up costs which are very high due to the use of expensive materials for their construction. In that respect, we describe a cost-effective alkaline fuel cell (AFC) that uses solid, polymer based, membrane instead of conventionaly used, highly concentrated, corrosive, liquid alkaline electrolyte. This approach to AFC is potentially the basis of a simple, low-cost system, that can solve one of the problems of the highly-efficient and environment-friendly AFC.The focus of this paper are low cost composite alkaline membranes, based on poly(vinyl alcohol) (PVA). The PVA matrix is made by solution cast method and gamma irradiation crosslinking. Three different types of membranes are obtained in this manner - plain PVA membrane, PVA membrane cross-linked using gamma irradiation (γ-PVA) and composite PVA membrane doped with Mo (PVA-Mo). These membranes are immersed in the alkaline solution and investigated as anion exchange membranes. The performance of the solid alkaline fuel cells (SAFCs) containing these PVA membranes has been studied under hydrogen and oxygen gas flow on the Pt/C catalyst. Both, γ-PVA and PVA-Mo membranes are modified to absorb larger amounts of alkaline solution than the PVA membrane, thus greatly improving the performance of the SAFC, in terms of output power. This is clearly indicated in the polarisation curves. The electrochemical impedance spectroscopy measurements during the SAFC operation were also performed to give better insight in the effect observed. Investigation presented in this paper clearly indicates that solid alkaline PVA membranes can be used for the construction of the SAFCs.     

Temperature induced evolution of structure/microstructure parameters and their correlations with electric/magnetic properties of nanocrystalline Nickel ferrite

Nickel ferrite nanoparticles were annealed in order to find dependence of electric/magnetic properties on crystallite size. The following correlations of crystallite size with physical parameters were found: (a) lattice parameter decreases with the increase in size and it reaches value for bulk counterpart approximately for crystallites bigger than 7 nm, (b) ac electrical resistivity at room temperature increases with the increase in crystallite size, (c) for crystallites of ~7 nm or smaller electrical resistivity have maximum value at 50 °C, (d) the real part of permittivity at selected frequency generally decreases with the increase in crystallite size and (e) magnetization increases with the increase in crystallite size. Deviation of stoichiometry, cation polyvalence, and cation redistribution with annealing are the main factors that influence physical properties of Nickel ferrite nanoparticles.     

Development and Application of a Decision Support System for Human Reliability Assessment – A Case Study of an Electric Power Company

This paper describes the human reliability assessment using absolute probability judgment (APJ) method in the Electric Power Company of Serbia (EPS). Taking into account conventional APJ approach, a new decision support tool EPS‐APJ was developed. The EPS‐APJ tool is intended for use by a group of experts for human error probability assessment. The basic goal of the tool is to facilitate the process of decision‐making by experts, in the complex environment of the electric power companies. The usefulness of this new tool is approved in a case study of use of the EPS‐APJ for the purpose of the analysis of a repair intervention on a 10/0.4‐kV steel lattice tower ‘Nogaje’, in the EPS. For the purpose of this study, a database on work‐related injuries, accidents, and critical interventions occurred over a 10‐year period was created. The research comprised analysis of 1074 workplaces, with the total of 3997 employees. The case study performed at the EPS has confirmed that the EPS‐APJ tool for quantification of human errors is highly applicable, comprehensive, and simple to use. Comparison of the results obtained by application of the EPS‐APJ tool versus the basic APJ method has confirmed the accuracy of the decision support tool, and significant speed advantage in conducting an expert evaluation. Copyright © 2015 John Wiley & Sons, Ltd.     

Linear computational complexity robust ILC for lifted systems

In this paper we propose a new methodology to synthesize and implement robust monotonically convergent ILC for lifted systems, with the computational complexity that is linear in the trial length. Starting from the model uncertainty of the local sample to sample LTI or LTV models, and using the randomized algorithm, we compute the bound on the model uncertainty of the ILC system representation in the trial domain (lifted ILC). Based on this computed uncertainty bound, we design weighting matrices of the Norm Optimal ILC, such that the robust monotonic convergence condition is satisfied. Since we compute the uncertainty bound, rather than assuming its value in the trial domain, we reduce the conservatism of the robust design. The linear computational complexity of the algorithms for computation of the uncertainty bound and implementation of the Norm Optimal ILC law, is achieved through exploiting the sequentially semi-separable structure of the lifted system matrices. Therefore the framework proposed in this paper is especially suitable for the LTI and LTV uncertain systems with a large number of samples in the trial. We have performed numerical experiments to demonstrate the robustness and linear computational complexity of the proposed method.     

Thiol‐ene photofunctionalization of 1,4‐polymyrcene

1,4‐Polymyrcene was synthesized by anionic polymerization of β‐myrcene and was subjected to photochemical functionalization with various thiols (i.e. methyl thioglycolate, methyl 3‐mercaptopropionate, butyl 3‐mercaptopropionate, ethyl 2‐mercaptopropionate and 2‐methyl‐2‐propanethiol) using benzophenone/UV light as the radical source. The yield of thiol addition to the trisubstituted double bonds of 1,4‐polymyrcene decreased in the order 1° thiol (ca 95%) > 2° thiol (ca 80%) > 3° thiol (<5%), due to the reversibility of the thiol‐ene reaction. Remarkably, thiol addition to the side‐chain double bonds was 8 ? 10 times (1° thiol) or 24 times (2° thiol) faster than to the main‐chain double bonds, which can be explained by the different accessibility of the double bonds and steric hindrance. Despite the use of a 10‐fold excess of thiol with respect to myrcene units, the thiol‐ene addition was accompanied by chain coupling reactions, which in the extreme case of 3° thiol (or in the absence of thiol) resulted in the formation of insoluble crosslinked material. As an example, a methyl‐thioglycolate‐functionalized 1,4‐polymyrcene was saponified/crosslinked to give submicron polyelectrolyte particles in dilute alkaline solution. © 2018 Society of Chemical Industry     

Hybrid Colloidal Heterostructures of Anisotropic Semiconductor Nanocrystals Decorated with Noble Metals: Synthesis and Function

This Feature Article offers an overview of hybrid colloidal heterostructures of anisotropic semiconductor nanocrystals decorated with metals; primarily gold and platinum. The nonspherical shapes of the semiconductor components create a great variety of metal‐decorated hybrid nanostructures, whose synthesis and morphology are considered here. Due to the current interest in photocatalytic systems able to utilize solar energy for water‐splitting, the use of Pt‐decorated CdS‐based nanorods for hydrogen generation is specifically addressed. Great flexibility of the colloidal synthesis leading to well‐defined hybrid semiconductor–metal nanostructures drastically increases the possibility of their integration into functional nanosystems with novel synergetic properties, making them promising candidates for a variety of photovoltaic, catalytic, and sensing applications.     

Tuning of BiFeO3 multiferroic properties by light doping with Nb

Bulk ceramic samples of BiFeO₃ were light doped (up to 1%) with Nb⁵⁺ in the place of Fe³⁺ (B-site doping) and their multiferroic properties were investigated using XRD, SEM, polarization (PMTS) and magnetization (SQUID) techniques. It is shown that even the small percentages of doping can notably change electric and magnetic behavior. Electric conductivity differs by two orders of magnitude between samples doped with 0.2% and 1% Nb. The ferroelectric behavior strongly depended on conduction mechanism, and transition from space-charge-limited current (SCLC) conduction to trap-filled limited (TFL) conduction regime reflected on a change in hysteresis patterns, particularly for the samples with 0.2% and 0.5% Nb. Separation of ZFC-FC magnetization curves occurred for all Nb concentrations and increased with Nb doping. Weak ferromagnetic behavior and the increase of remnant magnetization with Nb concentration was observed from the hysteresis measurements. Coercive field changed drastically compared to the pure BiFeO₃, namely, the sample with 1% Nb exhibited very high coercive magnetic field of ~ 10?kOe.     

Predicting body fat percentage based on gender,age and BMI by using artificial neural networks

In the human body, the relation between fat and fat-free mass (muscles, bones etc.) is necessary for the diagnosis of obesity and prediction of its comorbidities. Numerous formulas, such as Deurenberg et al., Gallagher et al., Jackson and Pollock, Jackson et al. etc., are available to predict body fat percentage (BF%) from gender (GEN), age (AGE) and body mass index (BMI). These formulas are all fairly similar and widely applicable, since they provide an easy, low-cost and non-invasive prediction of BF%. This paper presents a program solution for predicting BF% based on artificial neural network (ANN). ANN training, validation and testing are done by randomly divided dataset that includes 2755 subjects: 1332 women (GEN = 0) and 1423 men (GEN = 1), with AGE from 18 to 88 y and BMI from 16.60 to 64.60 kg/m². BF% was estimated by using Tanita bioelectrical impedance measurements (Tanita Corporation, Tokyo, Japan). ANN inputs are: GEN, AGE and BMI, and output is BF%. The predictive accuracy of our solution is 80.43%. The main goal of this paper is to promote a new approach to predicting BF% that has same complexity and costs but higher predictive accuracy than above-mentioned formulas.