X-ray propagation in carbon nanotubes

The maintenance of the growth of the multibillion-dollar semiconductor industry requires the development of techniques for the fabrication and characterisation of nanoscale devices. Consequently, there is great interest in photolithography techniques such as extreme UV and x-ray. Both of these techniques are extremely expensive and technologically very demanding. In this paper we describe research on the feasibility of exploiting x-ray propagation within carbon nanotubes (CNT's) for the fabrication and characterisation of nanoscale devices. This work discusses the parameters determining the design space available. To demonstrate experimentally the feasibility of x-ray propagation, arrays of carbon nanotubes have been grown on silicon membranes. The latter are required to provide structural support for the CNT's while minimising energy loss. To form a waveguide metal is deposited between the nanotubes to block x-ray transmission in this region at the same time as cladding the CNT's. The major challenge has been to fill the spaces between the CNT's with material of sufficient thickness to block x-ray transmission while maintaining the structural integrity of the CNT's. Various techniques have been employed to fill the gaps between the nanotubes including electroplating, sputtering and evaporation. This work highlights challenges encountered in optimising the process.

Content Based Integration of Construction Site Images in AEC/FM Model Based Systems

The Architecture, Engineering, Construction and Facilities Management (AEC/FM) industry is rapidly becoming a multidisciplinary, multinational and multi-billion dollar economy, involving large numbers of actors working concurrently at different locations and using heterogeneous software and hardware technologies. Since the beginning of the last decade, a great deal of effort has been spent within the field of construction IT in order to integrate data and information from most computer tools used to carry out engineering projects. For this purpose, a number of integration models have been developed, like web-centric systems and construction project modeling, a useful approach in representing construction projects and integrating data from various civil engineering applications. In the modern, distributed and dynamic construction environment it is important to retrieve and exchange information from different sources and in different data formats in order to improve the processes supported by these systems. Previous research demonstrated that a major hurdle in AEC/FM data integration in such systems is caused by its variety of data types and that a significant part of the data is stored in semi-structured or unstructured formats. Therefore, new integrative approaches are needed to handle non-structured data types like images and text files. This research is focused on the integration of construction site images. These images are a significant part of the construction documentation with thousands stored in site photographs logs of large scale projects. However, locating and identifying such data needed for the important decision making processes is a very hard and time-consuming task, while so far, there are no automated methods for associating them with other related objects. Therefore, automated methods for the integration of construction images are important for construction information management. During this research, processes for retrieval, classification, and integration of construction images in AEC/FM model based systems have been explored. Specifically, a combination of techniques from the areas of image and video processing, computer vision, information retrieval, statistics and content-based image and video retrieval have been deployed in order to develop a methodology for the retrieval of related construction site image data from components of a project model. This method has been tested on available construction site images from a variety of sources like past and current building construction and transportation projects and is able to automatically classify, store, integrate and retrieve image data files in inter-organizational systems so as to allow their usage in project management related tasks.