Effects of carbon nanotubes and metal catalysts on hydrogen storage in magnesium nanocomposites

This paper reports a study on nanostructured magnesium composites with carbon nanotubes (CNTs) and catalytic transition metals with high H-2 adsorption capacity and fast adsorption kinetics at reduced hydrogenation temperatures. Nanostructures in such a composite are shown to be responsible for improvements in both adsorption capacity and kinetics. It is found that the carbon nanotubes significantly increase the hydrogen storage capacity, and the catalytic transition metals (Fe and Ti) greatly improve the kinetics. This could be understood from the enhancement of diffusion by CNTs and decrease in energy barrier of hydrogen dissociation at the magnesium surface.

Omnigen:providing electricity, food preparation, cold storage and pure water using a variety of local fuels

We describe a polygeneration system that can run on neat plant oils, such as Jatropha and Pongamia, or standard diesel fuel. A prototype has been constructed using a compression ignition engine of 9.9 kW shaft output. It consumes 3 L/h of fuel and will produce 40 kg/h of ice by means of an adsorption refrigerator powered from the engine jacket heat. Steaming of rice, deep and shallow frying, and other types of food preparation heated by the exhaust gas have been demonstrated. In addition, the feasibility of producing distilled water by means of multiple-effect distillation powered by the engine waste heat is shown. Overall plant efficiency and potential savings in greenhouse gas emissions are discussed. © 2012 Elsevier Ltd.

Control of second-life hybrid battery energy storage system based on modular boost-multilevel buck converter

To fully utilize second-life batteries on the grid system, a hybrid battery scheme needs to be considered for several reasons: the uncertainty over using a single source supply chain for second-life batteries, the differences in evolving battery chemistry and battery configuration by different suppliers to strive for greater power levels, and the uncertainty of degradation within a second-life battery. Therefore, these hybrid battery systems could have widely different module voltage, capacity, and initial state of charge and state of health. In order to suitably integrate and control these widely different batteries, a suitable multimodular converter topology and an associated control structure are required. This paper addresses these issues proposing a modular boost-multilevel buck converter based topology to integrate these hybrid second-life batteries to a grid-tie inverter. Thereafter, a suitable module-based distributed control architecture is introduced to independently utilize each converter module according to its characteristics. The proposed converter and control architecture are found to be flexible enough to integrate widely different batteries to an inverter dc link. Modeling, analysis, and experimental validation are performed on a single-phase modular hybrid battery energy storage system prototype to understand the operation of the control strategy with different hybrid battery configurations.

Analysis and design of power management scheme for an on-board solar energy storage system

This paper investigates the power management issues in a mobile solar energy storage system. A multi-converter based energy storage system is proposed, in which solar power is the primary source while the grid or the diesel generator is selected as the secondary source. The existence of the secondary source facilitates the battery state of charge detection by providing a constant battery charging current. Converter modeling, multi-converter control system design, digital implementation and experimental verification are introduced and discussed in details. The prototype experiment indicates that the converter system can provide a constant charging current during solar converter maximum power tracking operation, especially during large solar power output variation, which proves the feasibility of the proposed design. © 2014 IEEE.

Efficient storage and domain-specific information discovery on semistructured documents

The increasing amount of available semistructured data demands efficient mechanisms to store, process, and search an enormous corpus of data to encourage its global adoption. Current techniques to store semistructured documents either map them to relational databases, or use a combination of flat files and indexes. These two approaches result in a mismatch between the tree-structure of semistructured data and the access characteristics of the underlying storage devices. Furthermore, the inefficiency of XML parsing methods has slowed down the large-scale adoption of XML into actual system implementations. The recent development of lazy parsing techniques is a major step towards improving this situation, but lazy parsers still have significant drawbacks that undermine the massive adoption of XML. ^ Once the processing (storage and parsing) issues for semistructured data have been addressed, another key challenge to leverage semistructured data is to perform effective information discovery on such data. Previous works have addressed this problem in a generic (i.e. domain independent) way, but this process can be improved if knowledge about the specific domain is taken into consideration. ^ This dissertation had two general goals: The first goal was to devise novel techniques to efficiently store and process semistructured documents. This goal had two specific aims: We proposed a method for storing semistructured documents that maps the physical characteristics of the documents to the geometrical layout of hard drives. We developed a Double-Lazy Parser for semistructured documents which introduces lazy behavior in both the pre-parsing and progressive parsing phases of the standard Document Object Model’s parsing mechanism. ^ The second goal was to construct a user-friendly and efficient engine for performing Information Discovery over domain-specific semistructured documents. This goal also had two aims: We presented a framework that exploits the domain-specific knowledge to improve the quality of the information discovery process by incorporating domain ontologies. We also proposed meaningful evaluation metrics to compare the results of search systems over semistructured documents. ^