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Strategien zur Zustandserfassung von Kanalisationen. Aachener Schriften zur Stadtentwässerung. Bd 7
(2006)
Development of an optimized LSO/LuYAP phoswich detector head for the Lausanne ClearPET demonstrator
(2006)
This paper describes the LSO/LuYAP phoswich detector head developed for the ClearPET small animal PET scanner demonstrator that is under construction in Lausanne within the Crystal Clear Collaboration. The detector head consists of a dual layer of 8×8 LSO and LuYAP crystal arrays coupled to a multi-anode photomultiplier tube (Hamamatsu R7600-M64). Equalistion of the LSO/LuYAP light collection is obtained through partial attenuation of the LSO scintillation light using a thin aluminum deposit of 20-35 nm on LSO and appropriate temperature regulation of the phoswich head between 30°C to 60°C. At 511keV, typical FWHM energy resolutions of the pixels of a phoswich head amounts to (28±2)% for LSO and (25±2)% for LuYAP. The LSO versus LuYAP crystal identification efficiency is better than 98%. Six detector modules have been mounted on a rotating gantry. Axial and tangential spatial resolutions were measured up to 4 cm from the scanner axis and compared to Monte Carlo simulations using GATE. FWHM spatial resolution ranges from 1.3 mm on axis to 2.6 mm at 4 cm from the axis.
Quartz crystal nanobalance (QCN) sensors are considered as powerful masssensitive sensors to determine materials in the sub-nanogram level. In this study, a single piezoelectric quartz crystal nanobalance modified with polystyrene was employed to detect benzene, toluene, ethylbenzene and xylene (BTEX compounds). The frequency shift of the QCN sensor was found to be linear against the BTEX compound concentrations in the range about 1-45 mg l-1. The correlation coefficients for benzene, toluene, ethylbenzene, and xylene were 0.991, 0.9977, 0.9946 and 0.9971, respectively. The principal component analysis was also utilized to process the frequency response data of the single piezoelectric crystal at different times, considering to the different adsorption-desorption dynamics of BTEX compounds. Using principal component analysis, it was found that over 90% of the data variance could still be explained by use of two principal components (PC1 and PC2). Subsequently, the successful identification of benzene and toluene was possible through the principal component analysis of the transient responses of the polystyrene modified QCN sensor. The results showed that the polystyrene-modified QCN had favorable identification and quantification performances for the BTEX compounds.
Hands-on-training in high technology areas is usually limited due to the high cost for lab infrastructure and equipment. One specific example is the field of MEMS, where investment and upkeep of clean rooms with microtechnology equipment is either financed by production or R&D projects greatly reducing the availability for education purposes. For efficient hands-on-courses a MEMS training foundry, currently used jointly by six higher education institutions, was established at FH Kaiserslautern. In a typical one week course, students manufacture a micromachined pressure sensor including all lithography, thin film and packaging steps. This compact and yet complete program is only possible because participants learn to use the different complex machines in advance via a Virtual Training Lab (VTL). In this paper we present the concept of the MEMS training foundry and the VTL preparation together with results from a scientific evaluation of the VTL over the last three years.