# Molecularly Imprinted Filtering Adsorbents for Odor Sensing
## 1 Introduction  
With progress in organic materials, electronics, and micro-fabrication technologies, a number of highly advanced odor sensors have been proposed. However, compared with physical or chemical sensors such as inertial [1] or blood glucose sensors [2], commercial application of these odor sensors is not widespread. A major reason for this is the complexity of the analytes that make up an odor. An odor usually consists of a mixture of several gases, and the possible number of combinations of these gases is enormous. One of the simplest approaches for the detection and discrimination of odors is to use a large number of odor-specific sensors in an array; this is known as the electronic nose (e-nose) approach. However, it is often impossible to prepare such large numbers of odor-specific sensors as an array. In contrast, it has recently been reported that the human nose can discriminate a single odor from over one trillion odors [3]. When animals smell odors, the olfactory bulb is activated by stimulation of the olfactory receptors. This information from the activated olfactory bulb is called an odor map [4, 5], and it is composed of several hundreds of glomeruli on the olfactorybulb. Glomeruli activated by odorants with similar molecular characteristics are located close together, and form an odor cluster [6; 7; 8; 9]. With the resulting cluster map, a huge number of odors can easily be discriminated. The generation of odor cluster maps thus enables the measurement of odors in the same manner as that used in animal olfaction. Each cluster corresponds to a particular type of molecular structure information, for example functional groups, molecular sizes, or shapes, and recognizing the molecular structure of the odorant enables qualitative and quantitative analysis of the odor based on its visible pattern information [10; 11; 12]. Thus, the design and flexible control of the sensor specificity toward parameters based on odor cluster maps are important factors for odor sensor development. In our previous study, we developed a gas sensing system aimed at recognizing complex molecular structures using a gas concentrating-separating sensing device [13]. It was possible to regenerate odor maps from sensor responses to odorants using this system. The system had eight sensing cells, and each cell consisted of an adsorbent separation unit and a gas sensing unit; the adsorbent separation unit contained an adsorbent film on a micro-ceramic heater, and the separated odorants were quantified with a gas sensing unit made up of a metal oxide semiconductor gas sensor. Figure 1 shows the conceptual design of this odor sensing system. The selectivity of this device depends on the molecular recognition properties of the adsorbents; it requires adsorbents with high selectivity in molecular recognition. The sensor system can selectively detect odors if it incorporates adsorbents with appropriate selectivities for various odorants. However, the ability of the previously used adsorbents was insufficient for the recognition of a wide variety of odor molecules. In this study, a new molecular selective adsorbent for gas preconcentrator was developed by combinations of adsorbent materials and a molecularly imprinted polymer (MIP). First, we focused on polydimethylsiloxane (PDMS), which has superior fabrication processability and a high adsorption capacity and specificity for odorants, as confirmed in our previous work. In addition, other adsorbent polymers, such as divinylbenzene copolymer (DVB) and polyvinyl alcohol (PVA), were compounded into a matrix with a PDMS substrate, with the aim of controlling the solubility parameters of the adsorbents. A polyvinyl chloride (PVC)--containing plasticizer was also examined. To improve the selectivity of the adsorbents toward the odor molecules, the surface of the adsorbent substrates was modified with a molecularly imprinted filter (MIF), which is an MIP layer formed by a sol-gel method, in which the MIP retains molecular void space in its structure.