Gas Storage Scale-up at Room Temperature on High Density Carbon Materials

In relation to the current interest on gas storage demand for environmental applications (e.g., gas transportation, and carbon dioxide capture) and for energy purposes (e.g., methane and hydrogen), high pressure adsorption (physisorption) on highly porous sorbents has become an attractive option. Considering that for high pressure adsorption, the sorbent requires both, high porosity and high density, the present paper investigates gas storage enhancement on selected carbon adsorbents, both on a gravimetric and on a volumetric basis. Results on carbon dioxide, methane, and hydrogen adsorption at room temperature (i.e., supercritical and subcritical gases) are reported. From the obtained results, the importance of both parameters (porosity and density) of the adsorbents is confirmed. Hence, the densest of the different carbon materials used is selected to study a scale-up gas storage system, with a 2.5 l cylinder tank containing 2.64 kg of adsorbent. The scale-up results are in agreement with the laboratory scale ones and highlight the importance of the adsorbent density for volumetric storage performances, reaching, at 20 bar and at RT, 376 g l-1, 104 g l-1, and 2.4 g l-1 for CO2, CH4,and H2, respectively.

Electrocatalytic hydrogenation of acetophenone using a Polymer Electrolyte Membrane Electrochemical Reactor

The use of a solid polymeric electrolyte, spe, is not commonly found in organic electrosynthesis despite its inherent advantages such as the possible elimination of the electrolyte entailing simpler purification processes, a smaller sized reactor and lower energetic costs. In order to test if it were possible to use a spe in industrial organic electrosynthesis, we studied the synthesis of 1-phenylethanol through the electrochemical hydrogenation of acetophenone using Pd/C 30 wt% with different loadings as cathode and a hydrogen gas diffusion anode. A Polymer Electrolyte Membrane Electrochemical Reactor, PEMER, with a fuel cell structure was chosen to carry out electrochemical reduction with a view to simplifying an industrial scale-up of the electrochemical process. We studied the influence of current density and cathode catalyst loading on this electroorganic synthesis. Selectivity for 1-phenylethanol was around 90% with only ethylbenzene and hydrogen detected as by-products.

Realizing the Commercial Potential of Hierarchical Zeolites: New Opportunities in Catalytic Cracking

Many approaches to mesoporous zeolites have been reported. The preparation of mesoporous zeolite Y, as the most widely used zeolite in catalysis, its properties, and its application in fluid catalytic cracking (FCC) and hydrocracking are reviewed. Finally, the scale-up and use of mesostrutured zeolite Y on an industrial scale are described, as the first commercial application of hierarchical zeolites.

Applications for CO2-Activated Carbon Monoliths: I. Gas Storage

Carbon monoliths with high densities are studied as adsorbents for the storage of H2, CH4, and CO2 at ambient temperature and high pressures. The starting monolith A3 (produced by ATMI Co.) was activated under a CO2 flow at 1073 K, applying different activation times up to 48 h. Micropore volumes and apparent surface areas were deduced from N2 and CO2 adsorption isotherms at 77 K and 273 K, respectively. CO2 and CH4 isotherms were measured up to 3 MPa and H2 up to 20 MPa. The BET surface area of the starting monolith (941 m2/g) could be significantly increased up to 1586 m2/g, and the developed porosity is almost exclusively comprised of micropores <1 nm. Total storage amounts take into account the compressed gas in the void space of the material, in addition to the adsorbed gas. Remarkably, high total storage amounts are reached for CO2 (482 g/L), CH4 (123 g/L), and H2 (18 g/L). These values are much higher than for other sorbents with similar surface areas, due to the high density of the starting monolith and of the activated ones, for which the density decreases only slightly (from 1.0 g/cm3 to 0.8 g /cm3 upon CO2 activation). The findings reveal the suitability of high density activated carbon monoliths for gas storage application. Thus, the amounts of stored gas can be increased by more than a 70 % in the case of H2 at 20 MPa, almost 5.5 times in the case of CH4 at 3 MPa, and more than 7.5 times in the case of CO2 at 3 MPa when adsorbents are used for gas storage under the investigated conditions rather than simple compression. Furthermore, the obtained results have been recently confirmed by a scale-up study in which 2.64 kg of high density monolith adsorbent was filled a tank cylinder of 2.5 L (Carbon, 76, 2014, 123).

Sol–Gel Coordination Chemistry: Building Catalysts from the Bottom-Up

The development of synthetic routes for the tailoring of efficient silica-based heterogeneous catalysts functionalized with coordination complexes or metallic nanoparticles has become a important goal in chemistry. Most of these techniques have been based on postsynthetic treatments of preformed silicas. Nevertheless, there is an emerging approach, so-called sol–gel coordination chemistry, based on co-condensation during the sol–gel preparation of the hybrid material of the corresponding complex or nanoparticle modified with terminal trialkoxysilane groups with a silica source (such as tetraethoxysilane) and in the presence of an adequate surfactant. This method leads to the production of new mesoporous metal complex-silica materials, with the metallic functionality incorporated homogeneously into the structure of the hybrid material, improving the stability of the coordination complex (which is protected by the silica network) and reducing the leaching of the active phase. This technique also offers the actual possibility of functionalizing silica or other metal oxides for a wider range of applications, such as photonics, sensing, and biochemical functions.

Analyzing the commercial activities of a street network by ranking their nodes: a case study in Murcia, Spain

Urban researchers and planners are often interested in understanding how economic activities are distributed in urban regions, what forces influence their special pattern and how urban structure and functions are mutually dependent. In this paper, we want to show how an algorithm for ranking the nodes in a network can be used to understand and visualize certain commercial activities of a city. The first part of the method consists of collecting real information about different types of commercial activities at each location in the urban network of the city of Murcia, Spain. Four clearly differentiated commercial activities are studied, such as restaurants and bars, shops, banks and supermarkets or department stores, but obviously we can study other. The information collected is then quantified by means of a data matrix, which is used as the basis for the implementation of a PageRank algorithm which produces a ranking of all the nodes in the network, according to their significance within it. Finally, we visualize the resulting classification using a colour scale that helps us to represent the business network.

Feature selection by multi-objective optimisation: Application to network anomaly detection by hierarchical self-organising maps

Feature selection is an important and active issue in clustering and classification problems. By choosing an adequate feature subset, a dataset dimensionality reduction is allowed, thus contributing to decreasing the classification computational complexity, and to improving the classifier performance by avoiding redundant or irrelevant features. Although feature selection can be formally defined as an optimisation problem with only one objective, that is, the classification accuracy obtained by using the selected feature subset, in recent years, some multi-objective approaches to this problem have been proposed. These either select features that not only improve the classification accuracy, but also the generalisation capability in case of supervised classifiers, or counterbalance the bias toward lower or higher numbers of features that present some methods used to validate the clustering/classification in case of unsupervised classifiers. The main contribution of this paper is a multi-objective approach for feature selection and its application to an unsupervised clustering procedure based on Growing Hierarchical Self-Organising Maps (GHSOMs) that includes a new method for unit labelling and efficient determination of the winning unit. In the network anomaly detection problem here considered, this multi-objective approach makes it possible not only to differentiate between normal and anomalous traffic but also among different anomalies. The efficiency of our proposals has been evaluated by using the well-known DARPA/NSL-KDD datasets that contain extracted features and labelled attacks from around 2 million connections. The selected feature sets computed in our experiments provide detection rates up to 99.8% with normal traffic and up to 99.6% with anomalous traffic, as well as accuracy values up to 99.12%.

Conceptual Modelling of Complex Network Management Systems

Society, as we know it today, is completely dependent on computer networks, Internet and distributed systems, which place at our disposal the necessary services to perform our daily tasks. Moreover, and unconsciously, all services and distributed systems require network management systems. These systems allow us to, in general, maintain, manage, configure, scale, adapt, modify, edit, protect or improve the main distributed systems. Their role is secondary and is unknown and transparent to the users. They provide the necessary support to maintain the distributed systems whose services we use every day. If we don’t consider network management systems during the development stage of main distributed systems, then there could be serious consequences or even total failures in the development of the distributed systems. It is necessary, therefore, to consider the management of the systems within the design of distributed systems and systematize their conception to minimize the impact of the management of networks within the project of distributed systems. In this paper, we present a formalization method of the conceptual modelling for design of a network management system through the use of formal modelling tools, thus allowing from the definition of processes to identify those responsible for these. Finally we will propose a use case to design a conceptual model intrusion detection system in network.