A metal hydride–polymer composite for hydrogen storage applications

To address the issue of the breakdown into fine powders that occurs in the practical use of metal hydrides, the possibility of using a polymeric material as a matrix that contains the active metal particles was experimentally assessed. A ball milling approach in the tumbling mode was used to develop a metal hydride–polymer composite with a high metal to polymer weight ratio. The alloy powder was blended with the polymer and a coating of the metal particles was obtained. The composite was consolidated by hot pressing and the pellets were characterized in terms of their hydriding–dehydriding properties. The materials did not show significant losses in either loading capacity or kinetic properties. The polymeric matrix resulted as being stable under hydrogen cycling. Further, from SEM observation it was confirmed that the metal powders remained embedded in the polymeric matrix even after a number of cycles and that the overall dimensional integrity was retained.     

A model to design and optimize multi-energy systems in buildings at the design concept stage

Increasing interest is currently being addressed to multi-energy systems in buildings. These systems integrate different energy sources, at least one of which is renewable, in order to cover the thermal and electrical loads of a building. Since the design and operation of such systems are very complicated for many reasons (e.g. the intermittent nature of the renewable sources, the highly interlinked system layouts), it is of the foremost importance to provide tools to help select the best system configuration and energy sources mix.A modelling approach to multi-energy systems in buildings, based on the energy hub concept is presented in this work. This approach allows the coupling between the energy demand and the energy supply in a building to be modelled in a synthetic way. The model was customised to be used at the concept stage of the building design, either as a system simulation tool or as a system selection tool. If the prices and the characteristics of the energy converters and of the energy-wares are known, it is possible, with a certain set of constraints, to determine the configuration that minimises the initial investment costs, the use of non-renewable sources or the life-cycle costs. This approach makes it possible to avoid the simulation and ranking of a set of different system configurations, and also permits the study of the behaviour of such systems in an open configuration and not as individual systems. An application of the methodology to a case study is provided.     

e-Science, caGrid, and Translational Biomedical Research

Translational research projects target a wide variety of diseases, test many different kinds of biomedical hypotheses, and employ a large assortment of experimental methodologies. Diverse data, complex execution environments, and demanding security and reliability requirements make the implementation of these projects extremely challenging and require novel e-Science technologies.     

A combination of Monte Carlo simulation and cellular automata for computing the availability of complex network systems

This paper combines Monte Carlo simulation and cellular automata for computing the availability of a complex network system and the importance measures of its elements.     

Efficient unbalanced merge-sort

Sorting algorithms based on successive merging of ordered subsequences are widely used, due to their efficiency and to their intrinsically parallelizable structure. Among them, the merge-sort algorithm emerges indisputably as the most prominent method. In this paper we present a variant of merge-sort that proceeds through arbitrary merges between pairs of quasi-ordered subsequences, no matter which their size may be. We provide a detailed analysis, showing that a set of n elements can be sorted by performing at most n⌊logn⌋ key comparisons. Our method has the same optimal asymptotic time and space complexity as compared to previous known unbalanced merge-sort algorithms, but experimental results show that it behaves significantly better in practice.     

Modeling of Physical Defects in PN Junction Based Graphene Devices

Graphene’s exceptional electro-mechanical properties make it a strong contender to replace silicon-based Complementary Metal-Oxide Semiconductor (CMOS) devices in the future. Among other novel material-based devices, graphene is pushing the research community to find new technological solutions that exploit its special characteristics. As it is a semimetal, the key challenge for graphene-based devices to be used in digital circuits is introducing band gap. Among the proposed approaches, electrostatic doping represents a key option. It allows the implementation of graphene pn junctions through which building a new class of reconfigurable logic gates is possible. This devices are analyzed in this work. Recent works presented a quantitative analysis of such gates in terms of area, delay and power consumptions, confirming their superiority w.r.t. CMOS technologies below the 22 nm. This paper explores another dimension, that is testability, and proposes a study of possible physical defects that might alter the functionality of the graphene logic gates. Two major kinds of manufacturing defects, which are possible in these gates, namely the S h o r t s between the device’s terminals and O p e n terminals, are considered. These faults have been injected into non faulty devices at the SPICE-level and the resulting behavior is mapped to appropriate fault model. Most of such models belong to the CMOS domain, but for some specific class of defects, new fault definitions are needed.     

CO2 separation and landfill biogas upgrading: A comparison of 4A and 13X zeolite adsorbents

CO₂ separation from wet and dry synthetic biogas has been investigated using adsorption on 4A and 13X molecular sieves in dynamic conditions, flowing through fixed beds in an adsorption column connected with an IR detector. The adsorption of CO₂ has also been investigated by IR spectroscopy over pressed disks of the zeolites in static dry and wet conditions. 13X molecular sieve has significant adsorption capacity of CO₂ from dry biogas, which is further increased by the presence of moisture. This is due to the change of the adsorption mode of CO₂ due to the copresence of water. Over wet 13X zeolite adsorption of CO₂ mostly occurs in the form of bicarbonate ions interacting with coadsorbed water, while over the dry surface several different kinds of carbonate ions are formed together with molecular adsorbed species. The adsorption capacity of CO₂ from biogas is definitely lower over 4A molecular sieve, where coadsorption of methane is also significant. However, regeneration of 4A by purging with nitrogen at r.t. is faster than that of 13X. Over 4A coadsorption of water do modifies the adsorption state of CO₂ but has little effect on adsorption capacity.     

Reliability and accuracy of embedded fiber Bragg grating sensors for strain monitoring in advanced composite structures

This work investigated issues for an efficient and reliable embedding and use of Fiber Bragg Grating (FBG) sensors for strain monitoring of composite structures with particular regard to the manufacturing process of components in the nautical field by means of the vacuum bag technique in autoclave. CFRP material laminates with embedded FBGs were produced and the effect of the curing process parameters on the light transmission characteristics of the optical fibers was initially investigated. Two different types of coating, namely polyimide and acrylate, were tested by measuring the light attenuation by an Optical Time Domain Reflectometer. Tensile specimens were subsequently extracted from the laminas and instrumented also with a surface-mounted conventional electrical strain gage (SG). Comparison between the FBG and SG measurements during static tensile tests allowed the evaluation of the strain monitoring capability of the FBGs, in particular of their sensitivity (i.e., gage factor) when embedded.     

Constrained combinatorial optimization of multi-layered composite structures by means of Stud GA with proportionate selection and extinction

In this paper a revised algorithm, derived by the Stud GA, to optimize the stacking sequence of layered composite structures is presented. The constrained combinatorial problem is formulated and hence solved by means of the algorithm presented herein. Unlike the Stud GA, the proposed algorithm uses a fitness-proportionate selection to find potential mates to the Stud and a self-adaptive extinction to avoid premature convergence. Elitism is also allowed. Standard benchmark problems have been used to fully assess the validity of the proposed algorithm. Results in terms of reliability and efficiency are compared against three GAs and a Permutation Search (PS) algorithm. It has been demonstrated, by means of a parametric study, that a low probability of extinction is sufficient to ensure fast convergence as well as reliable results. Finally the optimization of a more complex aeronautic structure is addressed aiming to prove the validity of the proposed algorithm in a two level optimization strategy. Results in terms of efficiency are compared against those of an in-house standard GA.