Predictive Modelling and Mechanochemical Processing of New Mg-Based Hydrogen Storage Materials
Reference Number
GR/R82074/01
Title
Predictive Modelling and Mechanochemical Processing of New Mg-Based Hydrogen Storage Materials
Status
Completed
Energy Categories
Hydrogen and Fuel Cells(Hydrogen, Hydrogen storage)
Research Types
Basic and strategic applied research
Science and Technology Fields
PHYSICAL SCIENCES AND MATHEMATICS (Metallurgy and Materials)
UKERC Cross Cutting Characterisation
Not Cross-cutting
Principal Investigator
Professor ZX Guo
Chemistry
University College London
Chemistry
University College London
Award Type
Standard
Funding Source
EPSRC
Start Date
01 December 2002
End Date
30 November 2005
Duration
36 months
Total Grant Value
£210,456
Industrial Sectors
Energy
Region
London
Programme
Metals Programme -- Materials, Mechanical and Medical Eng
Other Investigator
Dr Y Song, Engineering and Materials Science, Queen Mary University of London
Industrial Collaborator
Project Contact, QinetiQ Ltd
Project Contact, DSTL - Defence Science and Technology Laboratory
Project Contact, Workers Educational Association
Project Contact, DSTL - Defence Science and Technology Laboratory
Project Contact, Workers Educational Association
Web Site
Objectives
Abstract
Limited fossil fuels C02 induced global warming, and vehicle-related air pollution are causing a worldwide drive to develop alternative/clean energyresources, much of which depending on the safe storage of hydrogen in a solid of sufficient capacity and high charging/discharging kinetics at low temperature /pressure. Many experimental investigations of H-storage systems have been carried out in the past, but mainly by trial and error, and thesystems are unsatisfactory for current industrial requirements. Mg-based hydrides hold great promise among various candidates, but suffer from low kinetics and high dissociation temperature. Here, the proposal aims to clarify scientifically the effects of chemical alloying and processing on H storagecharacteristics of Mg-based materials using both artificial neural network (statistic) and electronic structural (deterministic) simulations; and to develop technologically a mechanochemical powder metallurgy route to synthesise finely/nano- structuredhydrogen storage materials of desirable phase composition, H-storage capacity, dissociation temperature, kinetics, and cycle life, guided by model predictions. A range of processing and characterisation techniques, including a novel powder coating method, will be used to process, evaluate and optimise the storage materials
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Added to Database
01/01/07
