Biosensors for Odor Detection: A Review.

Animals can easily detect hundreds of thousands of odors in the environment with high sensitivity and selectivity. With the progress of biological olfactory research, scientists have extracted multiple biomaterials and integrated them with different transducers thus generating numerous biosensors. Those biosensors inherit the sensing ability of living organisms and present excellent detection performance.

Active Tracking of Temporally Changing Gas-Phase Odor Mixture Using an Array of Cells Expressing Olfactory Receptors.

A cell expressing an olfactory receptor (OR) exhibits excellent odorant detection ability and thus is widely applied in odor biosensors. Most of those biosensors, however, could detect only liquid-phase nonchanging single-component odorants. In this paper, we raised up an odor biosensor for the active tracking of temporally changing gas-phase odor mixture by an array of cells expressing ORs.

Array of Miniaturized Amperometric Gas Sensors Using Atomic Gold Decorated Pt/PANI Electrodes in Room Temperature Ionic Liquid Films.

Miniaturized sensors possess many advantages, such as rapid response, easy chip integration, a possible lower concentration of target compound detection, etc. However, a major issue reported is a low signal response. In this study, a catalyst, the atomic gold clusters of Au where n = 2, was decorated at a platinum/polyaniline (Pt/PANI) working electrode to enhance the sensitivity of butanol isomers gas measurement.

Extraction of sensing data for desired scent impressions using mass spectra of odorant molecules.

Most of the olfactory perception works focused on forward prediction of odor impression, for example, given an odorant's molecular structure parameters or the sensing data predict its odor impression. So far, mapping of mass spectrum of odorant molecules into the odor perception space (binary or continuous sensory space) has been successfully performed. However, it is difficult to predict odorant's sensing data associated with binary odor descriptors (e.

Exploration of sensing data to realize intended odor impression using mass spectrum of odor mixture.

Recently, olfactory information on odorants has been associated with their corresponding molecular features. Such information has been obtained by predicting the sensory test evaluation scores from the molecular structure parameters or the sensing data. On the other hand, we develop a method of the prediction of molecular features corresponding to the odor impression.

Predicting individual perceptual scent impression from imbalanced dataset using mass spectrum of odorant molecules.

Predicting odor impression is considered an important step towards measuring the quality of scent in the food, perfume, and cosmetic industries. In odor impression identification and classification, the main target is to predict scent impression while identifying non-target odor impressions are less significant. However, the effectiveness of predictive models depends on the quality of data distribution.

Extending lifetime of gas-phase odor biosensor using liquid thickness control and liquid exchange.

In recent few years, researchers utilized cell expressing olfactory receptor for vapor detection under various sensing mechanisms. Those olfactory systems, however, have relatively short lifetime due to the dry out of aqueous solution covering the cell. In this paper, we came up with a feedback control structure composed of an impedance measurement circuit, a microcontroller and two syringe pumps for maintaining thin liquid layer above cell.

Binary mixture quantification using cell-based odor biosensor system with active sensing.

Organisms perceive odorants in the environment through the use of a large number of olfactory receptors. Various odor biosensors have been researched and developed in order to mimic this olfactory mechanism. This study examines the quantification of odorant concentrations through the use of a sensor array comprised of several types of cell-based odor sensors expressing insect olfactory receptors with nonlinear characteristics.

Study of Room Temperature Ionic Liquids as Gas Sensing Materials in Quartz Crystal Microbalances.

Twenty-eight quartz crystal microbalance (QCM) sensors coated with different sensing films were tested and analyzed in this work; twenty-three sensors were coated in different room temperature ionic liquids (RTILs) and five additional QCM sensors were coated with conventional films commonly used as stationary phases in gas chromatography. Four volatile organic compounds (VOCs), in gaseous phase-hexanol, butyl acetate, 2-hexanone, and hexanoic acid-were measured. Two transducer mechanisms were used; resonant frequency shift and resistance shift of a QCM Mason equivalent circuit.

Indirect Sensing of Lower Aliphatic Ester Using Atomic Gold Decorated Polyaniline Electrode.

Novel sensing materials have been formed by decorating polyaniline conducting polymers with atomic gold clusters where the number of atoms is precisely defined. Such materials exhibit unique electrocatalytic properties of electrooxidation to aliphatic alcohols, although analytes with other functional groups have not been studied. This paper reports a study of cyclic voltammetric patterns obtained with bi-atomic gold nanocomposite response to analytes with other functional groups for sensor applications.

Predicting human odor perception represented by continuous values from mass spectra of essential oils resembling chemical mixtures.

There have been recent advances in predicting odor characteristics using molecular structure parameters of chemicals. Although the molecular structure parameters are available for each chemical, they cannot be used for chemical mixtures. This study will elucidate a computational method of predicting human odor perception from the mass spectra of chemical mixtures such as essential oils.

On-Line Mixture Quantification to Track Temporal Change of Composition Using FAIMS.

This paper reports on-line mixture quantification with FAIMS. Ternary gas mixtures composed of acetone, ethanol, and diethyl ether were used for quantification. We succeeded in an on-line quantification of ppm-level concentration and even sub-ppm-level gases using the gradient descent method.

Optimization of Modulation Methods for Solenoid Valves to Realize an Odor Generation System.

An artificial olfactory system coupled with an odor generation system is herein reported. The artificial olfactory system is composed of four chemical sensors consisting of quartz crystal microbalances (QCMs) coated with room temperature ionic liquids (RTILs). The sensors are interrogated by four vector network analyzers, which are used to measure the series resonant frequency and motional resistance.

An Olfactory Sensor Array for Predicting Chemical Odor Characteristics from Mass Spectra with Deep Learning.

Machine learning techniques are useful for applications such as electronic nose (e-nose) systems to classify or identify the target odor. In recent years, deep learning is regarded as one of the most powerful machine learning methods. It enables researchers to extract useful features automatically from high-dimensional raw data and has been widely applied to computer vision, speech recognition, and natural language processing, though little has been reported in the field of olfaction.

Ternary Gas Mixture Quantification Using Field Asymmetric Ion Mobility Spectrometry (FAIMS).

Gas mixture quantification is essential for the recording and reproducing odors, because an odor consists of multiple chemical compounds. Gas mixture quantification using field asymmetric ion mobility spectrometry (FAIMS) was studied. Acetone, ethanol, and diethyl ether were selected as components of a ternary gas mixture sample as representatives of the ketone, alcohol, and ether chemical classes, respectively.

Enhancement Method of Surface Acoustic Wave-Atomizer Efficiency for Olfactory Display.

Since olfaction is an important sense in human interfaces, we have developed an olfactory display using a surface acoustic wave (SAW) atomizer and micro-dispensers. In this olfactory display, the efficiency of atomization is important in order to avoid smell persistence problems often encountered in human olfactory interfaces. Thus, the SAW device is coated with amorphous Teflon film to change the substrate nature from hydrophilic to hydrophobic.

Correction: Predictive modeling for odor character of a chemical using machine learning combined with natural language processing.

[This corrects the article DOI: 10.1371/journal.pone.

Predictive modeling for odor character of a chemical using machine learning combined with natural language processing.

Recent studies on machine learning technology have reported successful performances in some visual and auditory recognition tasks, while little has been reported in the field of olfaction. In this paper we report computational methods to predict the odor impression of a chemical from its physicochemical properties. Our predictive model utilizes nonlinear dimensionality reduction on mass spectra data and performs the clustering of descriptors by natural language processing.

Odor Impression Prediction from Mass Spectra.

The sense of smell arises from the perception of odors from chemicals. However, the relationship between the impression of odor and the numerous physicochemical parameters has yet to be understood owing to its complexity. As such, there is no established general method for predicting the impression of odor of a chemical only from its physicochemical properties.

[Odor sensing system and olfactory display].

In this review, an odor sensing system and an olfactory display are introduced into people in pharmacy. An odor sensing system consists of an array of sensors with partially overlapping specificities and pattern recognition technique. One of examples of odor sensing systems is a halitosis sensor which quantifies the mixture composition of three volatile sulfide compounds.