Plasma enhanced chemical vapour deposition (PECVD) growth of carbon nanotubes and silicon nanowires has been studied in an Oxford Instruments Plasma Technology reactor. Typical growth regimes involve a catalyst pre-treatment step and a growth step where a precursor gas is decomposed to form the desired nanostructure. For both catalyst pre-treatment and nanostructure growth, utilising plasma gives advantages over other growth methods. During catalyst pre-treatment, a plasma step can promote formation of nanoparticles from a thin metal film, while also increasing the catalytic activity compared with thermal pre-treatment. In the case of carbon nanotube growth, PECVD can result in vertically aligned nanotubes where thermal CVD gave randomly ordered structures. Further, gas composition is seen to strongly affect the morphology and dimensions of the nanotubes grown. For Si nanowire growth PECVD can reduce the growth temperature, and enable the use of catalysts more compatible for fabrication of Si-based devices. In both cases catalyst particles are observed at the tips of the grown nanostructures, indicating a tip-growth mechanism.

The GridPP Collaboration is building a UK computing Grid for particle physics, as part of the international effort towards computing for the Large Hadron Collider. The project, funded by the UK Particle Physics and Astronomy Research Council (PPARC), began in September 2001 and completed its first phase 3 years later. GridPP is a collaboration of approximately 100 researchers in 19 UK university particle physics groups, the Council for the Central Laboratory of the Research Councils and CERN, reflecting the strategic importance of the project. In collaboration with other European and US efforts, the first phase of the project demonstrated the feasibility of developing, deploying and operating a Grid-based computing system to meet the UK needs of the Large Hadron Collider experiments. This note describes the work undertaken to achieve this goal.

CMS currently uses a number of tools to transfer data which, taken together, form the basis of a heterogeneous datagrid. The range of tools used, and the directed, rather than optimized nature of CMS recent large scale data challenge required the creation of a simple infrastructure that allowed a range of tools to operate in a complementary way. The system created comprises a hierarchy of simple processes (named 'agents') that propagate files through a number of transfer states. File locations and some application metadata were stored in POOL file catalogues, with LCG LRC or MySQL back-ends. Agents were assigned limited responsibilities, and were restricted to communicating state in a well-defined, indirect fashion through a central transfer management database. In this way, the task of distributing data was easily divided between different groups for implementation. The prototype system was developed rapidly, and achieved the required sustained transfer rate of ~10 MBps, with O(10 6 ) files distributed to 6 sites from CERN. Experience with the system during the data challenge raised issues with underlying technology (MSS write/read, stability of the LRC, maintenance of file catalogues, synchronization of filespaces), all of which have been successfully identified and handled. The development of this prototype infrastructure allows us to plan the evolution of backbone CMS data distribution from a simple hierarchy to a more autonomous, scalable model drawing on emerging agent and grid technology.

Distributed data transfer is currently characterised by the use of widely disparate tools, meaning that significant human effort is required to maintain the distributed system. In order to realise the possibilities represented by Grid infrastructure, the reality of a heterogenous computing environment must be tackled by providing means by which these disparate elements can communicate.Two such data distribution tools are the SRB and the EU DataGrid's Data Management fabric, both widely used by many large scientific projects. Both provide similar functionality the replication and cataloguing of datasets in a globally distributed environment. Significant quantities of data are currently stored in both. Moving data from the SRB to the EUDG, however, requires significant intervention and is therefore not scalable.This paper presents a mechanism by which the SRB can automatically interact with the GIGGLE framework as implemented by the EUDG, allowing access to SRB data using Grid tools. (C) 2004 Elsevier B.V. All rights reserved.