From Gas Sensors to Biomimetic Artificial Noses

Classification of Three Volatiles Using a Single-Type eNose with Detailed Class-Map Visualization

The use of electronic noses (eNoses) as analysis tools are growing in popularity; however, the lack of a comprehensive, visual representation of how the different classes are organized and distributed largely complicates the interpretation of the classification results, thus reducing their practicality. The new contributions of this paper are the assessment of the multivariate classification performance of a custom, low-cost eNose composed of 16 single-type (identical) MOX gas sensors for the classification of three volatiles, along with a proposal to improve the visual interpretation of the classification results by means of generating a detailed 2D class-map representation based on the inverse of the orthogonal linear transformation obtained from a PCA and LDA analysis. The results showed that this single-type eNose implementation was able to perform multivariate classification, while the class-map visualization summarized the learned features and how these features may affect the performance of the classification, simplifying the interpretation and understanding of the eNose results.

Recent Advances in Transistor-Based Bionic Perceptual Devices for Artificial Sensory Systems

The sensory nervous system serves as the window for human beings to perceive the outside world by converting external stimuli into distinctive spiking trains. The sensory neurons in this system can process multimodal sensory signals with extremely low power consumption. Therefore, new-concept devices inspired by the sensory neuron are promising candidates to address energy issues in nowadays’ robotics, prosthetics and even computing systems. Recent years have witnessed rapid development in transistor-based bionic perceptual devices, and it is urgent to summarize the research and development of these devices. In this review, the latest progress of transistor-based bionic perceptual devices for artificial sense is reviewed and summarized in five aspects, i.e., vision, touch, hearing, smell, and pain. Finally, the opportunities and challenges related to these areas are also discussed. It would have bright prospects in the fields of artificial intelligence, prosthetics, brain-computer interface, robotics, and medical testing.

Assessing over Time Performance of an eNose Composed of 16 Single-Type MOX Gas Sensors Applied to Classify Two Volatiles

This paper assesses the over time performance of a custom electronic nose (eNose) composed of an array of commercial low-cost and single-type miniature metal-oxide (MOX) semiconductor gas sensors. The eNose uses 16 BME680 versatile sensor devices, each including an embedded non-selective MOX gas sensor that was originally proposed to measure the total volatile organic compounds (TVOC) in the air. This custom eNose has been used previously to detect ethanol and acetone, obtaining initial promising classification results that worsened over time because of sensor drift. The current paper assesses the over time performance of different classification methods applied to process the information gathered from the eNose. The best classification results have been obtained when applying a linear discriminant analysis (LDA) to the normalized conductance of the sensing layer of the 16 MOX gas sensors available in the eNose. The LDA procedure by itself has reduced the influence of drift in the classification performance of this single-type eNose during an evaluation period of three months.

Odorant-binding proteins of mammals

Odorant-binding proteins (OBPs) of vertebrates belong to the lipocalin superfamily and perform a dual function: solubilizing and ferrying volatile pheromones to the olfactory receptors, and complexing the same molecules in specialized glands and assisting their release into the environment. Within vertebrates, to date they have been reported only in mammals, apart from two studies on amphibians. Based on the small number of OBPs expressed in each species, on their sites of production outside the olfactory area and their presence in biological fluids known to be pheromone carriers, such as urine, saliva and sexual secretions, we conclude that OBPs of mammals are specifically dedicated to pheromonal communication. This assumption is further supported by the observation that some OBPs present in biological secretions are endowed with their own pheromonal activity, adding renewed interest to these proteins. Another novel piece of evidence is the recent discovery that glycosylation and phosphorylation can modulate the binding activity of these proteins, improving their affinity to pheromones and narrowing their specificity. A comparison with insects and other arthropods shows a completely different scenario. While mammalian OBPs are specifically tuned to pheromones, those of insects, which are completely different in sequence and structure, include carriers for general odorants in addition to those dedicated to pheromones. Additionally, whereas mammals adopted a single family of carrier proteins for chemical communication, insects and other arthropods are endowed with several families of semiochemical-binding proteins. Here, we review the literature on the structural and functional properties of vertebrate OBPs, summarize the most interesting new findings and suggest possible exciting future developments.

Sensing of Airborne Infochemicals for Green Pest Management: What Is the Challenge?

One of the biggest global challenges for our societies is to provide natural resources to the rapidly expanding population while maintaining sustainable and ecologically friendly products. The increasing public concern about toxic insecticides has resulted in the rapid development of alternative techniques based on natural infochemicals (ICs). ICs (e.g., pheromones, allelochemicals, volatile organic compounds) are secondary metabolites produced by plants and animals and used as information vectors governing their interactions. Such chemical language is the primary focus of chemical ecology, where behavior-modifying chemicals are used as tools for green pest management. The success of ecological programs highly depends on several factors, including the amount of ICs that enclose the crop, the range of their diffusion, and the uniformity of their application, which makes precise detection and quantification of ICs essential for efficient and profitable pest control. However, the sensing of such molecules remains challenging, and the number of devices able to detect ICs in air is so far limited. In this review, we will present the advances in sensing of ICs including biochemical sensors mimicking the olfactory system, chemical sensors, and sensor arrays (e-noses). We will also present several mathematical models used in integrated pest management to describe how ICs diffuse in the ambient air and how the structure of the odor plume affects the pest dynamics.

Resolving Cross-Sensitivity Effect in Fluorescence Quenching for Simultaneously Sensing Oxygen and Ammonia Concentrations by an Optical Dual Gas Sensor

Simultaneous sensing of multiple gases by a single fluorescent-based gas sensor is of utmost importance for practical applications. Such sensing is strongly hindered by cross-sensitivity effects. In this study, we propose a novel analysis method to ameliorate such hindrance. The trial sensor used here was fabricated by coating platinum(II) meso-tetrakis(pentafluorophenyl)porphyrin (PtTFPP) and eosin-Y dye molecules on both sides of a filter paper for sensing O₂ and NH₃ gases simultaneously. The fluorescent peak intensities of the dyes can be quenched by the analytes and this phenomenon is used to identify the gas concentrations. Ideally, each dye is only sensitive to one gas species. However, the fluorescent peak related to O₂ sensing is also quenched by NH₃ and vice versa. Such cross-sensitivity strongly hinders gas concentration detection. Therefore, we have studied this cross-sensitivity effect systematically and thus proposed a new analysis method for accurate estimation of gas concentration. Comparing with a traditional method (neglecting cross-sensitivity), this analysis improves O₂-detection error from −11.4% ± 34.3% to 2.0% ± 10.2% in a mixed background of NH₃ and N₂.

Insect odorant receptor-based biosensors: Current status and prospects

Whilst the senses of vision and hearing have been successfully automated and miniaturized in portable formats (e.g. smart phone), this is yet to be achieved with the sense of smell. This is because the sensing challenge is not trivial as it involves navigating a chemosensory space comprising thousands of volatile organic compounds. Distinct aroma recognition is based on detecting unique combinations of volatile organic compounds. In natural olfactory systems this is accomplished by employing odorant receptors (ORs) with varying specificities, together with combinatorial neural coding mechanisms. Attempts to mimic the remarkable sensitivity and accuracy of natural olfactory systems has therefore been challenging. Current portable chemical sensors for odorant detection are neither sensitive nor selective, prompting research exploring artificial olfactory devices that use natural OR proteins for sensing. Much research activity to develop OR based biosensors has concentrated on mammalian ORs, however, insect ORs have not been explored as extensively. Insects possess an extraordinary sense of smell due to a repertoire of odorant receptors evolved to interpret olfactory cues vital to the insects' survival. The potential of insect ORs as sensing elements is only now being unlocked through recent research efforts to understand their structure, ligand binding mechanisms and development of odorant biosensors. Like their mammalian counterparts, there are many challenges with working with insect ORs. These include expression, purification and presentation of the insect OR in a stable display format compatible with an effective transduction methodology while maintaining OR structure and function. Despite these challenges, significant progress has been demonstrated in developing OR-based biosensors which exploit insect ORs in cells, lipid bilayers, liposomes and nanodisc formats. Ultrasensitive and highly selective detection of volatile organic compounds has been validated by coupling these insect OR display formats with transduction methodologies spanning optical (fluorescence) and electrical (field effect transistors, electrochemical impedance spectroscopy) techniques. This review summarizes the current status of insect OR based biosensors and their future outlook.

Machine Learning Enhances the Performance of Bioreceptor-Free Biosensors

Since their inception, biosensors have frequently employed simple regression models to calculate analyte composition based on the biosensor's signal magnitude. Traditionally, bioreceptors provide excellent sensitivity and specificity to the biosensor. Increasingly, however, bioreceptor-free biosensors have been developed for a wide range of applications. Without a bioreceptor, maintaining strong specificity and a low limit of detection have become the major challenge. Machine learning (ML) has been introduced to improve the performance of these biosensors, effectively replacing the bioreceptor with modeling to gain specificity. Here, we present how ML has been used to enhance the performance of these bioreceptor-free biosensors. Particularly, we discuss how ML has been used for imaging, Enose and Etongue, and surface-enhanced Raman spectroscopy (SERS) biosensors. Notably, principal component analysis (PCA) combined with support vector machine (SVM) and various artificial neural network (ANN) algorithms have shown outstanding performance in a variety of tasks. We anticipate that ML will continue to improve the performance of bioreceptor-free biosensors, especially with the prospects of sharing trained models and cloud computing for mobile computation. To facilitate this, the biosensing community would benefit from increased contributions to open-access data repositories for biosensor data.

Principles of odor coding in vertebrates and artificial chemosensory systems

The biological olfactory system is the sensory system responsible for the detection of the chemical composition of the environment. Several attempts to mimic biological olfactory systems have led to various artificial olfactory systems using different technical approaches. Here we provide a parallel description of biological olfactory systems and their technical counterparts. We start with a presentation of the input to the systems, the stimuli, and treat the interface between the external world and the environment where receptor neurons or artificial chemosensors reside. We then delineate the functions of receptor neurons and chemosensors as well as their overall I-O relationships. Up to this point, our account of the systems goes along similar lines. The next processing steps differ considerably: while in biology the processing step following the receptor neurons is the "integration" and "processing" of receptor neuron outputs in the olfactory bulb, this step has various realizations in electronic noses. For a long period of time, the signal processing stages beyond the olfactory bulb, i.e., the higher olfactory centers were little studied. Only recently there has been a marked growth of studies tackling the information processing in these centers. In electronic noses, a third stage of processing has virtually never been considered. In this review, we provide an up-to-date overview of the current knowledge of both fields and, for the first time, attempt to tie them together. We hope it will be a breeding ground for better information, communication, and data exchange between very related but so far little connected fields.

A new non-classical fold of varroa odorant-binding proteins reveals a wide open internal cavity

Odorant-binding proteins (OBPs), as they occur in insects, form a distinct class of proteins that apparently has no closely related representatives in other animals. However, ticks, mites, spiders and millipedes contain genes encoding proteins with sequence similarity to insect OBPs. In this work, we have explored the structure and function of such non-insect OBPs in the mite Varroa destructor, a major pest of honey bee. Varroa OBPs present six cysteines paired into three disulphide bridges, but with positions in the sequence and connections different from those of their insect counterparts. VdesOBP1 structure was determined in two closely related crystal forms and appears to be a monomer. Its structure assembles five α-helices linked by three disulphide bridges, one of them exhibiting a different connection as compared to their insect counterparts. Comparison with classical OBPs reveals that the second of the six α-helices is lacking in VdesOBP1. Ligand-binding experiments revealed molecules able to bind only specific OBPs with a moderate affinity, suggesting that either optimal ligands have still to be identified, or post-translational modifications present in the native proteins may be essential for modulating binding activity, or else these OBPs might represent a failed attempt in evolution and are not used by the mites.

Concentrating Vapor Traces with Binary Brushes of Immiscible Polymers

Vapors in the air around us can provide useful information about our environment, but we need sensitive vapor sensors to access this information, especially because those vapors are often present at very low concentrations. We report molecular dynamics simulations of a concept that can significantly increase the sensitivity of vapor sensors at low concentrations. By coating the sensor surfaces with end-anchored immiscible polymers, surface-bound polymer blends are formed that can concentrate vapors, reaching sorption enhancements of more than one order of magnitude, especially at low vapor concentrations.

Market Perspectives and Future Fields of Application of Odor Detection Biosensors within the Biological Transformation-A Systematic Analysis

The technological advantages that biosensors have over conventional technical sensors for odor detection and the role they play in the biological transformation have not yet been comprehensively analyzed. However, this is necessary for assessing their suitability for specific fields of application as well as their improvement and development goals. An overview of biological basics of olfactory systems is given and different odor sensor technologies are described and classified in this paper. Specific market potentials of biosensors for odor detection are identified by applying a tailored methodology that enables the derivation and systematic comparison of both the performance profiles of biosensors as well as the requirement profiles for various application fields. Therefore, the fulfillment of defined requirements is evaluated for biosensors by means of 16 selected technical criteria in order to determine a specific performance profile. Further, a selection of application fields, namely healthcare, food industry, agriculture, cosmetics, safety applications, environmental monitoring for odor detection sensors is derived to compare the importance of the criteria for each of the fields, leading to market-specific requirement profiles. The analysis reveals that the requirement criteria considered to be the most important ones across all application fields are high specificity, high selectivity, high repeat accuracy, high resolution, high accuracy, and high sensitivity. All these criteria, except for the repeat accuracy, can potentially be better met by biosensors than by technical sensors, according to the results obtained. Therefore, biosensor technology in general has a high application potential for all the areas of application under consideration. Health and safety applications especially are considered to have high potential for biosensors due to their correspondence between requirement and performance profiles. Special attention is paid to new areas of application that require multi-sensing capability. Application scenarios for multi-sensing biosensors are therefore derived. Moreover, the role of biosensors within the biological transformation is discussed.

Responses of the Pheromone-Binding Protein of the Silk Moth Bombyx mori on a Graphene Biosensor Match Binding Constants in Solution

An electronic biosensor for odors was assembled by immobilizing the silk moth Bombyx mori pheromone binding protein (BmorPBP1) on a reduced graphene oxide surface of a field-effect transistor. At physiological pH, the sensor detects the B. mori pheromones, bombykol and bombykal, with good affinity and specificity. Among the other odorants tested, only eugenol elicited a strong signal, while terpenoids and other odorants (linalool, geraniol, isoamyl acetate, and 2-isobutyl-3-methoxypyrazine) produced only very weak responses. Parallel binding assays were performed with the same protein and the same ligands, using the common fluorescence approach adopted for similar proteins. The results are in good agreement with the sensor’s responses: bombykol and bombykal, together with eugenol, proved to be strong ligands, while the other compounds showed only poor affinity. When tested at pH 4, the protein failed to bind bombykol both in solution and when immobilized on the sensor. This result further indicates that the BmorPBP1 retains its full activity when immobilized on a surface, including the conformational change observed in acidic conditions. The good agreement between fluorescence assays and sensor responses suggests that ligand-binding assays in solution can be used to screen mutants of a binding protein when selecting the best form to be immobilized on a biosensor.

Swelling of Poly(methyl acrylate) Brushes in Acetone Vapor

Sensor platforms can benefit from the incorporation of polymer brushes since brushes can concentrate the analyte near the sensor surface. Brushes that absorb acetone vapor are of particular interest since acetone is an important marker for biological processes. We present a simple procedure to synthesize acetone-responsive poly(methyl acrylate) brushes. Using spectroscopic ellipsometry, we show that these brushes respond within seconds and swell by more than 30% when exposed to acetone vapor. Moreover, quartz crystal microbalance measurements demonstrate that the brushes can be exploited to increase the acetone detection sensitivity of sensors by more than a factor 6. Surprisingly, we find that the swelling ratio of the brushes in acetone vapor is independent of the grafting density and the degree of polymerization of the polymers in the brush. This is qualitatively different from swelling of the same brushes in liquid environments, where the swelling ratio decreases for increasing grafting densities. Yet, it indicates that the brushes are robust and reproducible candidates for implementation in vapor sensor systems.

Gas sensors based on mass-sensitive transducers. Part 2: Improving the sensors towards practical application

Within the framework outlined in the first part of the review, the second part addresses attempts to increase receptor material performance through the use of sensor systems and chemometric methods, in conjunction with receptor preparation methods and sensor-specific tasks. Conclusions are then drawn, and development perspectives for gravimetric sensors are discussed.

Peptides, DNA and MIPs in Gas Sensing. From the Realization of the Sensors to Sample Analysis

Detection and monitoring of volatiles is a challenging and fascinating issue in environmental analysis, agriculture and food quality, process control in industry, as well as in 'point of care' diagnostics. Gas chromatographic approaches remain the reference method for the analysis of volatile organic compounds (VOCs); however, gas sensors (GSs), with their advantages of low cost and no or very little sample preparation, have become a reality. Gas sensors can be used singularly or in array format (e.g., e-noses); coupling data output with multivariate statical treatment allows un-target analysis of samples headspace. Within this frame, the use of new binding elements as recognition/interaction elements in gas sensing is a challenging hot-topic that allowed unexpected advancement. In this review, the latest development of gas sensors and gas sensor arrays, realized using peptides, molecularly imprinted polymers and DNA is reported. This work is focused on the description of the strategies used for the GSs development, the sensing elements function, the sensors array set-up, and the application in real cases.

Prediction of Odor Concentration Emitted from Wastewater Treatment Plant Using an Artificial Neural Network (ANN)

The odor emitted from a wastewater treatment plant (WWTP) is an important environmental problem. An estimation of odor emission rate is difficult to detect and quantify. To address this, various approaches including the development of emission factors and measurement using a closed chamber have been employed. However, the evaluation of odor emission involves huge manpower, time, and cost. An artificial neural network (ANN) is recognized as an efficient method to find correlations between nonlinear data and prediction of future data based on these correlations. Due to its usefulness, ANN is used to solve complicated problems in various disciplines of sciences and engineering. In this study, a method to predict the odor concentration in a WWTP using ANN was developed. The odor concentration emitted from a WWTP was predicted by the ANN based on water quality data such as biological oxygen demand, dissolved oxygen, and pH. The water quality and odor concentration data from the WWTP were measured seasonally in spring, summer, and autumn and these were used as input variations to the ANN model. The odor predicted by the ANN model was compared with the measured data and the prediction accuracy was estimated. Suggestions for improving prediction accuracy are presented.

The Emergence of Insect Odorant Receptor-Based Biosensors

The olfactory receptor neurons of insects and vertebrates are gated by odorant receptor (OR) proteins of which several members have been shown to exhibit remarkable sensitivity and selectivity towards volatile organic compounds of significant importance in the fields of medicine, agriculture and public health. Insect ORs offer intrinsic amplification where a single binding event is transduced into a measurable ionic current. Consequently, insect ORs have great potential as biorecognition elements in many sensor configurations. However, integrating these sensing components onto electronic transducers for the development of biosensors has been marginal due to several drawbacks, including their lipophilic nature, signal transduction mechanism and the limited number of known cognate receptor-ligand pairs. We review the current state of research in this emerging field and highlight the use of a group of indole-sensitive ORs (indolORs) from unexpected sources for the development of biosensors.

A Perspective on Recent Advances in Piezoelectric Chemical Sensors for Environmental Monitoring and Foodstuffs Analysis

This paper provides a selection of the last two decades publications on the development and application of chemical sensors based on piezoelectric quartz resonators for a wide range of analytical tasks. Most of the attention is devoted to an analysis of gas and liquid media and to industrial processes controls utilizing single quartz crystal microbalance (QCM) sensors, bulk acoustic wave (BAW) sensors, and their arrays in e-nose systems. The unique opportunity to estimate several heavy metals in natural and wastewater samples from the output of a QCM sensor array highly sensitive to changes in metal ion activity in water vapor is shown. The high potential of QCM multisensor systems for fast and cost-effective water contamination assessments “in situ” without sample pretreatment is demonstrated.

Is It Possible to Predict the Odor of a Molecule on the Basis of its Structure?

The olfactory sense is the dominant sensory perception for many animals. When Richard Axel and Linda B. Buck received the Nobel Prize in 2004 for discovering the G protein-coupled receptors’ role in olfactory cells, they highlighted the importance of olfaction to the scientific community. Several theories have tried to explain how cells are able to distinguish such a wide variety of odorant molecules in a complex context in which enantiomers can result in completely different perceptions and structurally different molecules. Moreover, sex, age, cultural origin, and individual differences contribute to odor perception variations that complicate the picture. In this article, recent advances in olfaction theory are presented, and future trends in human olfaction such as structure-based odor prediction and artificial sniffing are discussed at the frontiers of chemistry, physiology, neurobiology, and machine learning.

Intelligent Control of Bulk Tobacco Curing Schedule Using LS-SVM- and ANFIS-Based Multi-Sensor Data Fusion Approaches

The bulk tobacco flue-curing process is followed by a bulk tobacco curing schedule, which is typically pre-set at the beginning and might be adjusted by the curer to accommodate the need for tobacco leaves during curing. In this study, the controlled parameters of a bulk tobacco curing schedule were presented, which is significant for the systematic modelling of an intelligent tobacco flue-curing process. To fully imitate the curer’s control of the bulk tobacco curing schedule, three types of sensors were applied, namely, a gas sensor, image sensor, and moisture sensor. Feature extraction methods were given forward to extract the odor, image, and moisture features of the tobacco leaves individually. Three multi-sensor data fusion schemes were applied, where a least squares support vector machines (LS-SVM) regression model and adaptive neuro-fuzzy inference system (ANFIS) decision model were used. Four experiments were conducted from July to September 2014, with a total of 603 measurement points, ensuring the results’ robustness and validness. The results demonstrate that a hybrid fusion scheme achieves a superior prediction performance with the coefficients of determination of the controlled parameters, reaching 0.9991, 0.9589, and 0.9479, respectively. The high prediction accuracy made the proposed hybrid fusion scheme a feasible, reliable, and effective method to intelligently control over the tobacco curing schedule.

Odorant-Binding Proteins as Sensing Elements for Odour Monitoring

Odour perception has been the object of fast growing research interest in the last three decades. Parallel to the study of the corresponding biological systems, attempts are being made to model the olfactory system with electronic devices. Such projects range from the fabrication of individual sensors, tuned to specific chemicals of interest, to the design of multipurpose smell detectors using arrays of sensors assembled in a sort of artificial nose. Recently, proteins have attracted increasing interest as sensing elements. In particular, soluble olfaction proteins, including odorant-binding proteins (OBPs) of vertebrates and insects, chemosensory proteins (CSPs) and Niemann-Pick type C2 (NPC2) proteins possess interesting characteristics for their use in sensing devices for odours. In fact, thanks to their compact structure, their soluble nature and small size, they are extremely stable to high temperature, refractory to proteolysis and resistant to organic solvents. Moreover, thanks to the availability of many structures solved both as apo-proteins and in complexes with some ligands, it is feasible to design mutants by replacing residues in the binding sites with the aim of synthesising proteins with better selectivity and improved physical properties, as demonstrated in a number of cases.