Molecularly Imprinted Filtering Adsorbents for Odor Sensing
AbstractVersatile odor sensors that can discriminate among huge numbers of environmental odorants are desired in many fields, including robotics, environmental monitoring, and food production. However, odor sensors comparable to an animal’s nose have not yet been developed. An animal’s olfactory system recognizes odor clusters with specific molecular properties and uses this combinatorial information in odor discrimination. This suggests that measurement and clustering of odor molecular properties (e.g., polarity, size) using an artificial sensor is a promising approach to odor sensing. Here, adsorbents composed of composite materials with molecular recognition properties were developed for odor sensing. The selectivity of the sensor depends on the adsorbent materials, so specific polymeric materials with particular solubility parameters were chosen to adsorb odorants with various properties. The adsorption properties of the adsorbents could be modified by mixing adsorbent materials. Moreover, a novel molecularly imprinted filtering adsorbent (MIFA), composed of an adsorbent substrate covered with a molecularly imprinted polymer (MIP) layer, was developed to improve the odor molecular recognition ability. The combination of the adsorbent and MIP layer provided a higher specificity toward target molecules. The MIFA thus provides a useful technique for the design and control of adsorbents with adsorption properties specific to particular odor molecules. View Full-Text
Share & Cite This Article
Shinohara, S.; Chiyomaru, Y.; Sassa, F.; Liu, C.; Hayashi, K. Molecularly Imprinted Filtering Adsorbents for Odor Sensing. Sensors 2016, 16, 1974.
Shinohara S, Chiyomaru Y, Sassa F, Liu C, Hayashi K. Molecularly Imprinted Filtering Adsorbents for Odor Sensing. Sensors. 2016; 16(11):1974.Chicago/Turabian Style
Shinohara, Sho; Chiyomaru, You; Sassa, Fumihiro; Liu, Chuanjun; Hayashi, Kenshi. 2016. "Molecularly Imprinted Filtering Adsorbents for Odor Sensing." Sensors 16, no. 11: 1974.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.