Filtern
Dokumenttyp
- Posterpräsentation (3) (entfernen)
Sprache
- Englisch (3)
Referierte Publikation
- nein (3)
Schlagworte
- Gas sensing (3) (entfernen)
Organisationseinheit der BAM
Fluorescence based sensing is a versatile approach for the trace analysis outside of the laboratory, requiring suitable sensor materials and their integration into sensing devices. The versatility of fluorophores as probes, especially in terms of the possibility to tailor their optical as well as their recognition properties by synthetic modifications in a wide range, renders them a superior active component for the preparation of optical sensor devices. Recent works at BAM in this field include, for example, the detection of nerve gas agents, illustrating impressively the aforementioned benefits of fluorophores in optical sensing applications.
In the interdisciplinary approach presented here, we target hazardous gases such as ammonia, benzene, and hydrogen sulfide, next to others, which pose a major threat to human health and environmental safety and for which the availability of a sensitive and reliable detection method is highly desirable.
The dyes presented follow a “turn-on” fluorescence schematic which allows for the selective and sensitive detection of the respective gaseous analyte. The immobilization of the probe in polymeric matrices is then the next step toward the fabrication of a prototype device for molecular sensing.
In industrial environments, airborne by-products such as dust and (toxic) gases, constitute a major risk for the worker’s health. Major changes in automated processes in the industry lead to an increasing demand for solutions in air quality management. Thus, occupational health experts are highly interested in precise dust and gas distribution models for working environments. For practical and economic reasons, high-quality, costly measurements are often available for short time-intervals only. Therefore, current monitoring procedures are carried out sparsely, both in time and space, i.e., measurement data are collected in single day campaigns at selected locations only. Real-time knowledge of contaminant distributions inside the working environment would also provide means for better and more economic control of air impurities. For example, the possibility to regulate the workspace’s ventilation exhaust locations can reduce the concentration of airborne contaminants by 50%.
To improve the occupational health and safety of (industrial) workplaces, this work aims for developing a swarm of gas-sensitive aerial nano robots for monitoring indoor air quality and for localizing potential emission sources.
In industrial environments, airborne by-products such as dust and (toxic) gases, constitute a major risk for the worker’s health. Major changes in automated processes in the industry lead to an increasing demand for solutions in air quality management. Thus, occupational health experts are highly interested in precise dust and gas distribution models for working environments. For practical and economic reasons, high-quality, costly measurements are often available for short time-intervals only. Therefore, current monitoring procedures are carried out sparsely, both in time and space, i.e., measurement data are collected in single day campaigns at selected locations only. Real-time knowledge of contaminant distributions inside the working environment would also provide means for better and more economic control of air impurities. For example, the possibility to regulate the workspace’s ventilation exhaust locations can reduce the concentration of airborne contaminants by 50%.
To improve the occupational health and safety of (industrial) workplaces, this work aims for developing a swarm of gas-sensitive aerial nano robots for monitoring indoor air quality and for localizing potential emission sources.