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In this paper, methods of surface modification of different supports, i.e. glass and polymeric beads for enzyme immobilisation are described. The developed method of enzyme immobilisation is based on Schiff’s base formation between the amino groups on the enzyme surface and the aldehyde groups on the chemically modified surface of the supports. The surface of silicon modified by APTS and GOPS with immobilised enzyme was characterised by atomic force microscopy (AFM), time-of-flight secondary ion mass spectroscopy (ToF-SIMS) and infrared spectroscopy (FTIR). The supports with immobilised enzyme (urease) were also tested in combination with microreactors fabricated in silicon and Perspex, operating in a flow-through system. For microreactors filled with urease immobilised on glass beads (Sigma) and on polymeric beads (PAN), a very high and stable signal (pH change) was obtained. The developed method of urease immobilisation can be stated to be very effective.
In this paper, methods of sample preparation for potentiometric measurement of phenylalanine are presented. Basing on the spectrophotometric measurements of phenylalanine, the concentrations of reagents of the enzymatic reaction (10 mM L-Phe, 0,4 mM NAD+, 2U L-PheDH) were determined. Then, the absorption spectrum of the reaction product, NADH, was monitored (maximum peak at 340 nm). The results obtained by the spectrophotometric method were compared with the results obtained by the colourimetry, using pH indicators. The above-mentioned two methods will be used as references for potentiometric measurements of phenylalanine concentration.
An H2O2 sensor for the application in industrial sterilisation processes has been developed. Therefore, automated sterilisation equipment at laboratory scale has been constructed using parts from industrial sterilisation facilities. In addition, a software tool has been developed for the control of the sterilisation equipment at laboratory scale. First measurements with the developed sensor set-up as part of the sterilisation equipment have been performed and the sensor has been physically characterised by optical microscopy and SEM.
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.