Carsten Siering

Supramolecular Approach for Sensing Caffeine by Fluorescence

The host–guest interaction of receptors based on triphenylene ketals with oxopurines influences their fluorescence properties and can be exploited for sensing caffeine; this gives a rapid and easy insight into the binding behavior of synthetic caffeine receptors and their guests. This approach also permits a first insight into a methanol-induced self-aggregation of the receptors.

Practical Strategies for Stable Operation of HFF-QCM in Continuous Air Flow

Currently there are a few fields of application using quartz crystal microbalances (QCM). Because of environmental conditions and insufficient resolution of the microbalance, chemical sensing of volatile organic compounds in an open system was as yet not possible. In this study we present strategies on how to use 195 MHz fundamental quartz resonators for a mobile sensor platform to detect airborne analytes. Commonly the use of devices with a resonant frequency of about 10 MHz is standard. By increasing the frequency to 195 MHz the frequency shift increases by a factor of almost 400. Unfortunately, such kinds of quartz crystals tend to exhibit some challenges to obtain a reasonable signal-to-noise ratio. It was possible to reduce the noise in frequency in a continuous air flow of 7.5 m/s to 0.4 Hz [i.e., σ(τ) = 2 × 10−9] by elucidating the major source of noise. The air flow in the vicinity of the quartz was analyzed to reduce turbulences. Furthermore, we found a dependency between the acceleration sensitivity and mechanical stress induced by an internal thermal gradient. By reducing this gradient, we achieved reduction of the sensitivity to acceleration by more than one decade. Hence, the resulting sensor is more robust to environmental conditions such as temperature, acceleration and air flow.

A security assistance system combining person tracking with chemical attributes and video event analysis

Timely recognition of threats can be significantly supported by security assistance systems that work continuously in time and call security personnel in case of anomalous events in the surveillance area. We are describing the concept and the realization of an indoor security assistance system for real-time decision support. The system consists of a computer vision module and a person classification module. The computer vision module provides a video event analysis of the entrance region in front of the demonstrator. After entering the control corridor, the persons are tracked, classified and potential threats are localized inside the demonstrator. Data for person classification are provided by chemical sensors detecting hazardous materials. Due to their limited spatio-temporal resolution, a single chemical sensor cannot localize this material and associate it with a person. We compensate this deficiency by fusing the output of multiple, distributed chemical sensors with kinematical data from laser-range scanners. Considering both the computer vision information and the results of the person classification affords the localization of threats and a timely reaction of security personnel.