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Nanostructures include various atomic arrangements, including nanospheres, nanotubes, nanobamboo and nanocolumns. Nanocolumns are regularly shaped, sometimes hollow, molecular columns that have applications as ultrasensitive molecular sensors owing to their large surface area.
Fire Detection
The latest government statistics (2014-2015) recorded 33,900 domestic fires in the UK, and in 69% of these a smoke alarm was fitted. These typically use a sensor that detects smoke molecules, which affect the conductivity of air molecules that have been charged by a radioactive source.
A new generation of fire detectors that sense the poisonous gases associated with combustion is of interest because it is usually the exposure to these compounds that causes fatalities. These gases include NO, H2, CO, CO2, HCl, HCN and volatile organic compounds; and are released at relevantly low temperatures, possibly before smoke is produced, hence the interest in their detection
Now, a team of Korean scientists have announced a selection of metal oxide sensors that can detect these gases faster than commercially available detectors; and potentially be used in a new line of ultra-sensitive fire detectors. Quite simply, the more sensitive the alarm is, the faster it can alert us to danger.
Why Nanocolumns?
As nanostructures, nanocolumns have an inherently high surface area to volume ratio, being highly porous structures makes them ideal as extremely sensitive gas sensors. Nanocolumns can be likened to the villi of the intestine; in this investigation, the diameter of the columns ranged from 40 – 66 nm, with a length ranging from 189 – 335 nm. All interactions of these metal oxide nanocolumns with other atoms affects their resistance, which can be recorded.
Why PVC?
The use of polyvinylchloride (PVC) in our homes is ubiquitous; it is found in furniture, toys and white goods. The use of PVC as the source of noxious gases is, therefore, an excellent model of the gas profile of a house fire.
Nanocolumn smoke sensors: Faster sensitivity
The Glancing Angle Deposition (GLAD) technique was used to synthesise highly porous nanocolumns using oxides NiO, WO3, SnO2 and In2O3. To test their sensitivities, PVC was heated and the resistance of the nanocolumn layer was timed and quantified.
- At 200 °C, PVC begins to breakdown and all the oxides tested gave some response, SnO2 was the most sensitive and the only detector to reach the threshold.
- At 350 °C, smoke was present and a marked increase in resistance across all the detectors was observed, all reaching threshold. All oxide detectors responded faster than the commercial sensor, apart from NiO; with SnO2 showing the fastest response.
The results of this investigation show that SnO2 nanocolumns offer the most sensitive gas detection of the oxides investigated and NiO detectors could measure gas concentrations over a higher range.
Nanocolumn visualisation
Nanocolumn dimensions were measured using a Hitachi SU-70 Field Emission Scanning Electron Microscope, using the built-in measuring system, enabling measurement to the nearest tenth of a nanometre.
The SU-70 produces beautifully complex images in the nanoscale. Analytical FE-SEM using the SU-70 combines the field-proven stability, high current, and brightness with the ultra-high resolution required for a multitude of analytical applications. The Duo-objective Lens designed with a semi-in-lens optics provides capabilities for a wide range of applications that require high-resolution image observation and analysis.
References
1. Robbie, K. & Brett, M. J. Sculptured thin films and glancing angle deposition: Growth mechanics and applications. J. Vac. Sci. Technol. A Vacuum, Surfaces, Film. 15, 1460–1465 (1997).
2. Hawkeye, M. M. M. & Brett, M. M. J. Glancing angle deposition: Fabrication, properties, and applications of micro- and nanostructured thin films. J. Vac. Sci. Technol. A Vacuum, Surfaces, Film. 25, 1317 (2007).
3. Lee, K., Shim, Y., Song, Y. G., Han, S. D. & Lee, Y. Highly Sensitive Sensors based on Metal-oxide Nanocolumns for Early Fire Detection. 1–10 doi:10.3390/s17020303
4. Image Credit: Shutterstock.com/GeorgyShafeev
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