Refine
Year of publication
- 2006 (64) (remove)
Institute
- Fachbereich Medizintechnik und Technomathematik (64) (remove)
Language
- English (64) (remove)
Document Type
- Conference Proceeding (30)
- Article (28)
- Book (3)
- Lecture (2)
- Part of a Book (1)
Keywords
- Biosensor (23)
- Technische Mechanik (2)
- biosensor (2)
- 3-nitrofluoranthene (1)
- BTEX compounds (1)
- Bauingenieurwesen (1)
- Biosensorik (1)
- Bruchmechanik (1)
- CAD (1)
- CO (1)
The applicability of differential pulse voltammetry (DPV) and adsorptive stripping voltammetry (AdSV) at a non-toxic meniscus-modified silver solid amalgam electrode (m-AgSAE) for the determination of trace amounts of genotoxic substances was demonstrated on the determination of micromolar and submicromolar concentrations of 3-nitrofluoranthene using methanol - 0.01 mol L-1 NaOH (9:1) mixture as a base electrolyte and of Ostazine Orange using 0.01 mol L-1 NaOH as a base electrolyte.
Study of swift heavy ion modified conduction polymer composites for application as gas sensor
(2006)
A polyaniline-based conducting composite was prepared by oxidative polymerisation of aniline in a polyvinylchloride (PVC) matrix. The coherent free standing thin films of the composite were prepared by a solution casting method. The polyvinyl chloride-polyaniline composites exposed to 120 MeV ions of silicon with total ion fluence ranging from 1011 to 1013 ions/cm2, were observed to be more sensitive towards ammonia gas than the unirradiated composite. The response time of the irradiated composites was observed to be comparably shorter. We report for the first time the application of swift heavy ion modified insulating polymer conducting polymer (IPCP) composites for sensing of ammonia gas.
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.
The Crystal Clear Collaboration has developed a modular system for a small animal PET scanner (ClearPET). The modularity allows the assembly of scanners of different sizes and characteristics in order to satisfy the specific needs of the individual member institutions. The system performs depth of interaction detection by using a phoswich arrangement combining LSO and LuYAP scintillators which are coupled to Multichannel Photomultipliers (PMTs). For each PMT a free running 40 MHz ADC digitizes the signal and the complete scintillation pulse is sampled by an FPGA and sent with 20 MB/s to a PC for preprocessing. The pulse provides information about the gamma energy and the scintillator material which identifies the interaction layer. Furthermore, the exact pulse starting time is obtained from the sampled data. This is important as no hardware coincidence detection is implemented. All single events are recorded and coincidences are identified by software. The system in Jülich (ClearPET Neuro) is equipped with 10240 crystals on 80 PMTs. The paper will present an overview of the data acquisition system.
The small animal PET scanners developed by the Crystal Clear Collaboration (ClearPETtrade) detect coincidences by analyzing timemarks which are attached to each event. The scanners are able to save complete single list mode data which allows analysis and modification of the timemarks after data acquisition. The timemarks are obtained from the digitally sampled detector pulses by calculating the baseline crossing of the rising edge of the pulse which is approximated as a straight line. But the limited sampling frequency causes a systematic error in the determination of the timemark. This error depends on the phase of the sampling clock at the time of the event. A statistical method that corrects these errors will be presented