Masahiro Imahashi

Concentrating materials covered by molecular imprinted nanofiltration layer with reconfigurability prepared by a surface sol–gel process for gas-selective detection

Sensors that recognize molecules are acquired for the comprehensive detection of great many kinds of gases. Adsorbents with high molecular recognition and condensation ability were developed for selective gas sensing with a molecular imprinting technique. Developed adsorbents have multilayer structures consisted of a chemically modified polymer layer on the surface of a substrate covered by a TiO2 gel monolayer by the surface sol-gel process. Ellipsometry measurements showed that the 6-nm-thick layers deposited on the substrate. Cavities of molecular templates were imprinted on these layers, and thus, the film acts as a molecular gas filter without concentrating ability, which could form specific binding sites for various molecules that confirmed using solid-phase microextraction and gas chromatography-mass spectrometry. Gases were selectively absorbed into an accumulating adsorption layer and other gas molecules were blocked by the nanofiltration. These developed adsorbents enabled effective concentration ability and the filtration of gases or odors. In addition, these filters possess the flexibility to be easily configured with specific surface properties to interact with volatile molecules under appropriate conditions. A successful multiplex filter, imprinted simultaneously on an adsorbent with different sites, was demonstrated.

Data fusion approach for human body odor discrimination using GC-MS spectra

This study deals with data fusion approach to search discriminating biomarker volatile organic chemicals (VOCs) in body odor for individual differentiation. Particularly we have employed kernel principal component analysis (KPCA) combined with majority voting method to build up novel data fusion strategy. Gas chromatography-mass spectrometry (GC-MS) characterizes human body odor samples to find out the VOCs composition (alcohols, acids, aldehydes, esters, ketones, carbonyl compounds, sulfides and hydrocarbons etc.). Peak number and related area value of VOCs from the GC-MS spectra of body odor extract is used for analysis. GC-MS data from three experiments, based on body odor samples of four persons (different age groups) in dissimilar conditions are collected. Optimal set of peak numbers are selected with fusion approach. Linear PCA is used in validation of elected peak numbers for discrimination of individuals body odor. The opted peaks result satisfactory differentiation of individuals body odor in feature space. Thereafter biomarker VOCs are affirmed by matching corresponding peak number in GC-MS spectra. Analysis outcomes conclude particular set of biomarker VOCs for each experiment.

Artificial odor map and discrimination of odorants using the odor separating system

In this research, achievement of the odor discrimination was examined. At first, odor separating system was developed which imitates the odor receptive mechanism of biological olfaction. A rough detection of odor becomes possible with this device. Therefore, this device makes it possible to measure the molecular size and the polarity of odorant and discriminate the mixed odor. Then, measuring representative odor molecules belonging to biological glomeruli clusters, odor information is extracted from time course patterns obtained by the system. The extracted features could be used for odor mapping close to the odor map created in the odor receptive mechanism which can classify odor quality by their odor cluster attributes.

Olfaction-Inspired Sensing Using a Sensor System with Molecular Recognition and Optimal Classification Ability for Comprehensive Detection of Gases

In this study, we examined the comprehensive detection of numerous volatile molecules based on the olfactory information constructed by using olfaction-inspired sensor technology. The sensor system can simultaneously detect multiple odors by the separation and condensation ability of molecularly imprinted filtering adsorbents (MIFAs), where a MIP filter with a molecular sieve was deposited on a polydimethylsiloxane (PDMS) substrate. The adsorption properties of MIFAs were evaluated using the solid-phase microextraction (SPME) and gas chromatography-mass spectrometry (GC-MS). The results demonstrated that the system embedded with MIFAs possesses high sensitivity and specific selectivity. The digitization and comprehensive classification of odors were accomplished by using artificial odor maps constructed through this system.

Discrimination of Body Odor Using Odor Sieving Sensor System

We have been focusing on sebum for discriminating human body odor. In this study, we examined body odor sampled from 12 male examinees. Through the experiment, we detected statistically‐significant differences between 56 pairs of examinees out of 66 pairs (approximately 85%). This result shows that our system and principle enabled discrimination of body odor between examinees to a certain extent.

Ultrathin reconfigurable molecular filter for gas-selective sensing

Development of a sensor system with high molecular recognition ability was examined for comprehensive detection of numerous volatiles. The built system extracts molecular profiles and classifies odor and VOCs by structurally discernible adsorbents with high selectivity and condensation ability. These adsorbents have multilayer structures where molecular imprinted filter was fabricated on various concentrating materials. Target molecules were selectively absorbed into concentrating layers and other gases were blocked by the nanofiltration. Therefore, the system embedded developed adsorbents enables the detection and discrimination of low-concentrated gases. In addition, nano-filters are optimized and tailored for various applications. These possess not only the flexibility to be easily reconfigured with different properties, but also specific properties to interact with a variety of volatiles. In this study, basic characteristics of molecular filters with reconfigurability was investigated by applying functional materials.

6.1.2 Artificial Odor Map and Cluster Sensing by MIP Adsorbents

In this study, we focused on an appropriate classification of different odorants like biological odor clustering and constructed the odor map by sensor technology to achieve the odor discrimination. First, an sensor system that imitates the odor receptive mechanism of biological olfaction was developed. With some adsorbents, this system enables high detection and discrimination of odor by obtaining molecular parameters of odorants. Odor features can be extracted by measuring representative odor materials that belong to different glomeruli clusters. For the purposes, we developed nano-filter adsorbents, called as molecular imprinted polymer adsorbents (MIPAs), which have high molecular recognition ability. MIPAs enable the classification of odorants into belonging odor clusters. Finally, we measured the selectivity of MIPAs used poly (acrylic acid) (PAA) or peptide as MIP layer. MIPAs make it possible odor clustering and the construction of odor map in the biological olfaction.