Original research objectives
VOC's recovery from water using a hybrid system combining a stripper and a membrane separation unit in a close loop. The research focussed on
a) organoselective membrane materials in relation with the VOC nature (water soluble, aromatic or chlorinated)
b) polymer optimisation and membrane module preparation, and
c) study of the integrated hybrid stripper-membrane process for dimethylketone, toluene and dichloromethane.
Polymers of interest to be synthesised and studied, including monomers, were:
- inorganic backbone polyphosphazene;
- rubbery materials containing dimethylsiloxane units;
- super glassy structures like poly[1-(trimethylsilyl)-1-propyne] PTMSP. Investigations of Sorption and Permeation characteristics for N2, VOC's as pure compounds or mixtures for a broad range of activity. The design, construction and modelling of a membrane module suitable to treat up to 1m3/h with gas flux up to 800 NL/h with low VOC concentration, i.e. 0.2-0.6 vol.
New organophilic membrane materials based on inorganic backbone polymers with improved selectivity of separation in relation to (organic vapour)/(water vapour)/air mixtures: basic data on selective gas/vapour transfer through membranes with balanced hydrophilic/organophilic properties. New composite membranes based on promising materials for application of gas phase wastewater decontamination and related hybrid prototype system construction New technological approach integrated with membrane technology to the treatment of waste water under low energy consumption and null contaminants release; theoretical modelling of gas phase process of different kinds of liquid purification; bench scale design and experimental results of suggested hybrid technology of VOCs recovery from water. Contractual technical issues & Publications.
A new platform for corporate information services IRAIA is a cross-provider service platform that enables information providers to establish an information service based on individual as well as thematically corporate information architectures. It focuses on opening up new opportunities for large-scale data collections to reach widespread audiences with innovative information. The retrieval of aggregated content-composed and semantically interlinked content of different type and from data collections-is one such opportunity, empowering users to conduct their own research whether for nice-to-know or need-to-know information. A first application area: economic information IRAIA's first application area is the domain of economic information.
Economic research institutes (ERI) and national statistical institutions (NSI) are by far the largest producers of economic information in Europe. Their data collections are renowned among a tiny expert community, but are so far an under-exploited asset, which could and should be a fundamental building block of new business opportunities in the content market. IRAIA can furnish these data with appeal that will be reflected by a more intensive use of these data by all kind of people working with economic information in different contexts ranging from mass media, SMEs, large companies, and banks, to universities, and even schools. Context-oriented searching and navigating Information arises from data when they are combined, arranged, and presented accordingly. Only a suitable combination of related time series and texts is in the position to convey the information that is contained in these separate and otherwise imperceptible components. Metadata expressing these content links are of outstanding importance when it comes to proliferate information that has to be composed by distributed and heterogeneous data. This holds for most of the large-scale and complex data collections in general, but for those of ERIs and NSIs in particular.
Providing orientation in a context starts with an expressive taxonomy as the lingua franca for economic information. For IRAIA we produced a powerful taxonomy that merges two of the most important structures in this field: eurostat's NACE nomenclature and the industry systematic of the ifo institute for economic research. The unified taxonomy creates a semantic coordinate system that enables exact and automatic positioning of coherent documents even if they are of different types. It also provides users with the necessary orientation while exploring the information space. Like in using languages it helps users as a passive vocabulary to identify the topics of their information problem. In IRAIA the user just points to relevant concepts displayed on the screen in order to initiate retrieval or to steer navigation. Just pointing to relevant terms is substantially easier than the active search for suitable concepts. The link of this interaction mode with IRAIA's architecture of orientation leads to the design of controlled concept queries implemented here for the first time in a large-scale retrieval environment. It does matter how fast and how easily people perform their retrieval tasks. A context-oriented search tool like IRAIA provides a coherent and comprehensive view on the whole information space as well as on the environment of the actual context focus. This is a key factor for the success of an information portal.
Fields of science
Call for proposalData not available
Funding SchemeCSC - Cost-sharing contracts
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