Optical Electronic Nose Research Articles

Integration of jackfruit seed-derived carbon dots and electronic nose for a sensitive detection of formaldehyde vapor

The preparation of carbon dots from jackfruit seeds through a pyrolysis method at 280℃ and their use for the detection of formaldehyde were reported. The as-prepared carbon dots showed a high fluorescence efficiency with a quantum yield of 12.7% and excellent photostability and dispersibility in aqueous solution with a zeta potential of ‒62.5 mV. The integration of carbon dot thin film and a home-made optical electronic nose system possessed sensitivity towards formaldehyde vapor with a detection limit of 24.7%v/v across a linear range of 25%v/v to 100%v/v. Furthermore, the sensor showed the highest sensitivity towards formaldehyde against other volatile organic compounds through a strong interaction between the carbonyl groups and the carbon dots. Additionally, principal component analysis (PCA) was conducted to achieve quantitative measurements of formaldehyde content in different formaldehyde volume ratios with substantial variance. Due to the significance of methanol as a typical chemical precursor for the industrial manufacturing of formaldehyde, the quantitative analytical method is essential to determining formaldehyde or methanol concentration. The sensing ability of carbon dot film-integrated electronic nose towards formaldehyde in formaldehyde/methanol mixtures was measured to be 10.74%v/v in a linear range of 25%v/v to 100%v/v. The PCA showed orderly linear combinations of the data set, which can be potentially utilized to analyze formaldehyde and methanol content in industrial processes. The results indicate the significant potential of carbon dots and optical electronic nose system as an effective formaldehyde sensing platform. Potential applications include the quantification of formaldehyde from methanol conversion and determination of methanol contaminant in formaldehyde.

Multipurpose fluorescent carbon dots from papaya seed waste as sensing materials for Cu2+ detection and diethyl ether vapor sensor via electronic nose system

Herein, carbon dots (CDs) as biocompatible, fluorescent carbon-based nanomaterials were synthesized from papaya seed waste as renewable carbon sources for the first time via a facile acid pyrolysis method. The papaya seed-derived CDs showed blue fluorescence emission under UV light (365 nm) with a quantum yield of 2.74%, and contained oxygen-, and nitrogen- containing functional groups. Due to their surface functionality, the CDs have a great potential for using as fluorescence sensing probe in metal ion sensing application. The CD solution exhibited the most selective detection to Cu2+ as presented the highest fluorescence quenching with the limit of detection (LOD) of 5.16 μM. The CD-paper-based fluorescent sensor was also developed for practical application, and the RGB value was used to compare the sensitivity of CDs toward metal ions. The CD sensing film was also prepared for diethyl ether vapor sensing via optical electronic nose system. The principal component analysis (PCA) score plots revealed the total variance of 99.3%, indicating that the CDs can be used to discriminate different concentrations of diethyl ether/ethanol vapor mixtures. This work demonstrated that the papaya seed-derived CDs have a great attention to be alternative materials for developing sensing materials in both solution and film forms.

Wavelength Dependence of Optical Electronic Nose for Ripeness Detection of Oil Palm Fresh Fruits

Electronic noses have been developed as an artificial sense to imitate the human nose based on volatile gases. They have been used in agriculture to monitor and predict fruit qualities such as ripeness and chemical contents. Electronic noses with semiconductor gas sensors have a limitation of volatile gases detected. Therefore, optical electronic noses using an output coupler become an alternative due to the wavelength dependency of the gas types. The ripeness of oil palm fresh fruit bunches (FFBs) is one of the main factors in determining the quality of crude palm oil. Electronic detection is preferable to substitute the manual methods for ripeness detection. This study built an optical electronic nose and analyzed the wavelength dependence on the detection performance. The electronic nose consisted of an infrared LED and a photodiode enclosed in a chamber, a microcontroller, and a sample chamber. We tested four infrared LEDs with 760, 780, 840, and 910 nm wavelengths. The samples were fruitlets taken from oil palm FFBs, previously categorized as unripe, ripe, and overripe. The fruits were grounded, inserted into the sample chamber, and preheated to increase the volatile gas concentration. Trapezoid areas represented the time-varying output voltages for each LED. The results showed that overripe fruits had slightly higher trapezoid areas. LED of 840 nm wavelength obtained higher trapezoid areas. LED of 780 nm was the best candidate for the electronic nose due to linearity in increasing trapezoid areas. The results showed the potential of the optical electronic nose for oil palm fruits.

A Novel Type of Feature Extraction Algorithm Based on Multi-Directional Analysis for Visual Optical Electronic Nose

According to the fact that the response images of a visual optical electronic nose (E-nose) have a huge amount of data, various frequency components and complex periodic and directional information, a novel type of visual optical E-nose (VOE-nose) feature extraction algorithm based on multi-directional analysis by directional filter bank (DFB) was proposed in this paper. Firstly, the gas sensing model of the VOE-nose was introduced, and the basic principle of DFB algorithm for feature extraction was described. Second, response images of NO2 in different wavebands were collected by the VOE-nose platform. Third, typical feature extraction and DFB feature extraction algorithms were used to extract features of response data, then the feature dimension reduction and pattern recognition algorithms were used to analyze the features. The mean classification accuracy is more than 95%, which verifies the superiority of the DFB feature extraction algorithm.

Development of a Tuneable NDIR Optical Electronic Nose.

Electronic nose (E-nose) technology provides an easy and inexpensive way to analyse chemical samples. In recent years, there has been increasing demand for E-noses in applications such as food safety, environmental monitoring and medical diagnostics. Currently, the majority of E-noses utilise an array of metal oxide (MOX) or conducting polymer (CP) gas sensors. However, these sensing technologies can suffer from sensor drift, poor repeatability and temperature and humidity effects. Optical gas sensors have the potential to overcome these issues. This paper reports on the development of an optical non-dispersive infrared (NDIR) E-nose, which consists of an array of four tuneable detectors, able to scan a range of wavelengths (3.1–10.5 μm). The functionality of the device was demonstrated in a series of experiments, involving gas rig tests for individual chemicals (CO2 and CH4), at different concentrations, and discriminating between chemical standards and complex mixtures. The optical gas sensor responses were shown to be linear to polynomial for different concentrations of CO2 and CH4. Good discrimination was achieved between sample groups. Optical E-nose technology therefore demonstrates significant potential as a portable and low-cost solution for a number of E-nose applications.

Independent Component Analysis-Based Baseline Drift Interference Suppression of Portable Spectrometer for Optical Electronic Nose of Internet of Things

The optical electronic nose (e-nose) is drawing more and more attention from the academia and industry in Internet of Things applications. Since the charge-coupled Device (CCD)-based portable spectrometer is commonly used in gas sensing system of e-nose, the baseline drift interference is easy to be introduced, which reduces the accuracy and sensitivity of the system and makes the sensing performance worse. For this issue, first, the baseline drift data are analyzed and the characteristics of the baseline drift interference brought by the portable spectrometer are found in this article. Then, according to the characteristics of the drift, a baseline drift suppression technique for portable spectrometer is proposed. Specifically, it mainly includes four steps: data preprocessing, dimension reduction using principal component analysis, sources separation using independent component analysis, and reconstruction after interference suppression. Finally, experimental results show that the proposed technique suppressed the interference effectively and even better compared with classical existing methods.

Label-free carbon dots from black sesame seeds for real-time detection of ammonia vapor via optical electronic nose and density functional theory calculation

Synthesis of carbon dots from natural precursors and their use in novel sensing applications currently gain much attention in the carbon dot research community because of its practicality and scaling-up possibility. Herein, carbon dots were synthesized from black sesame seeds via hydrothermal method and used as a dual-mode probe for the detection of ammonia in vapor and solution phases. The size of carbon dots was around 7.6 nm, and they exhibited blue-color emission under UV excitation in solution with a quantum yield of 2%. For the first time, the obtained carbon dots as a sensing layer were then used in optical electronic nose for the real-time, room-temperature detection of ammonia vapor and several volatile organic compounds. Our carbon dots in optical electronic nose could sense ammonia vapor generated from ammonia aqueous solutions with a detection limit of 0.8%v/v. Furthermore, they could also differentiate ammonia in various mixtures, containing methanol and water and from ethylenediamine and triethylamine. The density functional theory calculations were used to confirm the change in optical absorbance of carbon dots when exposed to solvent vapors. The computational results supported the experimental findings well in which the carbon dots and ammonia formed the most stable complex among all vapor molecules computed. A paper-based device was also constructed to prove the practicality and versatility of our carbon dot-based ammonia sensors. In summary, solid-state optical absorption sensing via electronic nose has proved to be a real-time, convenient approach for the detection of ammonia vapor. This work also demonstrates experimentally and computationally that the carbon dots are unique nanomaterials and the ammonia sensors based on carbon dots will be useful in various fields.

Utilization of carbon dots from jackfruit for real-time sensing of acetone vapor and understanding the electronic and interfacial interactions using density functional theory

Carbon dots are emerging carbon-based nanomaterials because of their unique optical properties, high surface area, and surface chelating functional groups. In this work, carbon dots were prepared from jackfruit using a one-step hydrothermal method and used as a sensing layer in an optical electronic nose for the real-time detection of acetone vapor at room temperature. The carbon dots showed blue photoluminescence with excitation-dependent fluorescence emission, excellent photostability, and a quantum yield of 5.2%. Using principal component analysis, the carbon dot-integrated electronic nose was able to distinguish acetone from hexane, ethanol, methanol, and water and between different concentrations of acetone in ethanol and aqueous solutions. From the time-dependent density functional theory calculations, an increase in carbon dot's extinction coefficients in bulk solvents was in a good agreement with the optical electronic nose results. The calculations of interaction energy using density functional theory method illustrated the electronic coupling and interfacial interactions between carbon dots and acetone and other volatile organic compounds. Interestingly, the unique ambipolar properties of carbon dots were computationally demonstrated. Furthermore, the photoluminescence of carbon dots was also exploited for the detection of acetone in aqueous solutions. Based on this work, our jackfruit-derived carbon dots were demonstrated to be versatile sensing materials for acetone in vapor and solution, and the computational methods highlighted the importance of interfacial electronic coupling towards unique sensing properties of carbon dots.

Multipurpose sensing applications of biocompatible radish-derived carbon dots as Cu2+ and acetic acid vapor sensors.

A recent trend in the preparation of carbon dots, optically unique nanomaterials, revolves around the use of readily-available, low-cost natural resources as precursors and their multipurpose applications. In this work, a hydrothermal method for preparing biocompatible carbon dots from radish was developed. The carbon dots were then tested for sensing of Cu2+ and acetic acid vapor. The carbon dots exhibited blue emission under UV illumination with, a quantum yield of 15%. The fluorescence emission was selectively quenched when Cu2+ ions were added, giving a detection limit of 0.16 μM. A paper-based fluorescent sensor was fabricated and shown to sense Cu2+ with a limit of detection of 6.8 μM. The carbon dots were able to determine the Cu2+ concentration in real water samples, with excellent recovery and reliability. The carbon dots were also used as the sensing material in an optical electronic nose, and tested for real-time detection of acetic acid vapor. Using principal component analysis, different ratios of acetic acid to methanol in solution were successfully identified with a detection limit of 15.5%. The acetic acid concentration in a real vinegar sample was also accurately determined. Our results demonstrated that label-free carbon dots derived from readily available radish can be simply used as versatile probes, giving them potential uses in multipurpose sensing applications.

Real-time detection of alcohol vapors and volatile organic compounds via optical electronic nose using carbon dots prepared from rice husk and density functional theory calculation

Rice husk, an agricultural waste that currently finds few uses, is rich in cellulose-based materials and silica. In this work, a simple one-pot method for preparing carbon dots and mesoporous silica from rice husk was developed, using hydrothermal and calcination methods. The carbon dots exhibited blue emission with excellent photostability, and had a diameter of 4–5 nm and a quantum yield of 3%. They were demonstrated to be capable of detecting alcohol vapors at room temperature, and of distinguishing between methanol, ethanol, and several volatile organic compounds when used as the sensing layer in an optical electronic nose system. The alcohol content of a commercial beverage was successfully determined using the carbon dot-integrated electronic nose. The solvation effect of the alcohol vapors on the electronic absorption spectra of model carbon dot structures was illustrated using time-dependent density functional theory with the dielectric polarizable continuum model. The UV–vis and computational results confirmed that the sensing mechanism of carbon dots is through the modulation of their optical absorbance governed by polar-polar interfacial interactions. This was experimental and computational demonstration of carbon dot sensing of vapors. Their excellent biocompatibility suggests biomedical applications, in addition to sensing. The production of two functional materials from a single low-value waste source was demonstrated.

Highly biocompatible yogurt-derived carbon dots as multipurpose sensors for detection of formic acid vapor and metal ions

Carbon dots are fascinating nanomaterials given their straightforward synthesis, unique optical properties, sensing capabilities, and biocompatibility. In this work, biocompatible carbon dots were prepared from yogurt using a two-step pyrolysis/hydrothermal method. The dots were spherical in shape with an average size of 4.7 nm. They showed blue emission under UV illumination with a quantum yield of 1.5%. Their photoluminescence was stable over three months and in both strong buffer solutions and highly concentrated salt solutions. The optical absorption and photoluminescence properties of the dots were employed for vapor and metal ion sensing, respectively. For the first time, the carbon dots were integrated into an optical electronic nose, and used for the detection of formic acid vapor at room temperature. Sensing was based on monitoring the optical transmission through a carbon dot film upon exposure to vapor, and the results were confirmed by UV–visible spectroscopy. The carbon dot-integrated electronic nose was able to distinguish vapor from formic acid/water solutions at different concentrations, with a detection limit of 7.3% v/v. The sensitivity of the dots to metal ions was tested by measuring the photoluminescence emission intensity at different excitation wavelengths. Principal component analysis was used to differentiate between the ions. The results suggested that interactions between carbon dots and metals ions occurred at a range of binding sites. The biocompability of the dots was demonstrated to be excellent. The study identified carbon dots produced from yogurt as multipurpose fluorescent nanomaterials with potential sensing and biomedical applications.

Highly fluorescent carbon dots from enokitake mushroom as multi-faceted optical nanomaterials for Cr6+ and VOC detection and imaging applications

Carbon dots are optically unique materials for sensing applications that can be prepared from various raw natural materials. In this work, highly fluorescent carbon dots were synthesized from enokitake mushroom via a one-step hydrothermal method in the presence of diluted sulfuric acid. The spherical carbon dots, with an average diameter of 4 nm, exhibited blue photoluminescence under UV illumination and a quantum yield of 11%, increasing to 39% upon passivation with tetraethylenepentamine. We employed both photoluminescence and light absorption properties of carbon dots for Cr6+ and volatile organic compound (VOC) sensing. Their fluorescence emission was selectively quenched by Cr6+ with a limit of detection of 0.73 µM. A fluorescent colorimetric paper-based device was fabricated and demonstrated to determine Cr6+ at concentrations as low as 10 µM. The carbon dots were also shown to have sensitivity and selectivity towards VOCs when integrated into an optical electronic nose. They were then used successfully to determine alcohol contents in aqueous solutions and ethanol concentration in a real spirit sample. They were further tested as a fingerprint detection agent and fluorophore for the manufacture of fluorescent plastics. Our results demonstrated that enokitake mushroom can be used to produce multi-faceted carbon dots with diverse applications.

Research on an optical e-nose denoising method based on LSSVM

Spectral noise has direct influences on the optical electronic nose (e-nose) to predicted effect and the detection accuracy of the test gas. In this paper, a spectral denoising method based on least squares support vector machine (LSSVM) was proposed after comprehensive analysis of spectral characteristics including small sample, non-linear, local extreme points and so on. The optical e-nose sensing data of NO2, SO2, C6H6 and C7H8 collected by the system were denoised by LSSVM. The normalized correlation coefficient (NCC) between the deniosed spectrum and the standard spectrum in HITRAN database is over 98%. Compared with the results of moving window average filtering (MWA), Savitzky-Golay filtering (SG) and wavelet threshold filtering, it is found that the waveform obtained by LSSVM can retain the information such as relative extreme value and width of the spectrum peak. The validity and superiority of LSSVM were verified by the experiment.

Tilapia fish microbial spoilage monitored by a single optical gas sensor

As consumption of fish and fish-based foods increases, non-destructive monitoring of fish freshness also becomes more prominent. Fish products are very perishable and prone to microbiological growth, not always easily detected by organoleptic evaluation. The analysis of the headspace of fish specimens through gas sensing is an interesting approach to monitor fish freshness. Here we report a gas sensing method for monitoring Tilapia fish spoilage based on the application of a single gas sensitive gel material coupled to an optical electronic nose. The optical signals of the sensor and the extent of bacterial growth were followed over time, and results indicated good correlation between the two determinations, which suggests the potential application of this simple and low cost system for Tilapia fish freshness monitoring.

Matrix Discriminant Analysis With Application to Colorimetric Sensor Array Data

With the rapid development of nano-technology, a “colorimetric sensor array” (CSA) that is referred to as an optical electronic nose has been developed for the identification of toxicants. Unlike traditional sensors that rely on a single chemical interaction, CSA can measure multiple chemical interactions by using chemo-responsive dyes. The color changes of the chemo-responsive dyes are recorded before and after exposure to toxicants and serve as a template for classification. The color changes are digitalized in the form of a matrix with rows representing dye effects and columns representing the spectrum of colors. Thus, matrix-classification methods are highly desirable. In this article, we develop a novel classification method, matrix discriminant analysis (MDA), which is a generalization of linear discriminant analysis (LDA) for the data in matrix form. By incorporating the intrinsic matrix-structure of the data in discriminant analysis, the proposed method can improve CSA’s sensitivity and more importantly, specificity. A penalized MDA method, PMDA, is also introduced to further incorporate sparsity structure in discriminant function. Numerical studies suggest that the proposed MDA and PMDA methods outperform LDA and other competing discriminant methods for matrix predictors. The asymptotic consistency of MDA is also established. R code and data are available online as supplementary material.

A novel spectrum analysis technique for odor sensing in optical electronic nose

With the advantages of light, such as high speed, high sensitivity, and wide response, the optical electronic nose draws more and more attention from the academia and industry. In an optical electronic nose, the optical gas sensing system is one of the crucial parts. In this study, optical gas sensing was realized by detecting the absorption spectrum of odors, where polychromatic light was employed to provide the sensing array according to its cross-sensitive and widely responsive to odors. To facilitate the odor identification of the electronic nose, the sensing responsive spectra of the optical gas sensing system were analyzed in this paper. Specifically, a feature-based analysis technique for the spectra in the form of two-dimensional matrix was firstly proposed. With the proposed spectrum analysis technique, the synthesized features of odors which are reflected by the sensing responsive spectra can be extracted. Afterwards, the theoretical validity of both the feature extraction and fault tolerance using the proposed feature-based spectrum analysis technique has been proved mathematically. Finally, nine hazardous gases were chosen in the experiments and the discrimination as well as fault-tolerant capability of the proposed feature-based spectrum analysis technique was experimentally demonstrated. Experiment results show that the proposed technique, compared with the counterpart techniques, has superior results on discriminating odors of similar response under noisy condition, which also indicates that the theoretical results and experimental results are consistent.

Optical Electronic Nose Based on Fe (III) Complex of Porphyrins Films for Detection of Volatile Compounds

Electronic nose is a device that attempts to mimic the living being smell system for detection of particular gases or volatile compounds. This paper reports the development of an optical electronic nose using Fe (III) based metalloporphyrins Langmuir-Blodgett thin films as sensing elements for discriminating four volatiles, 2-propanol, acetone, cyclohexane and ethanol. A multilayer feed forward neural network was developed to classify the input vectors from these two sensors. After the network being trained 100 times and introduced to blind samples, it was found that there are three fault decision for propanol, two for acetone, five for cyclohexane and one four ethanol, during 50 times being recognized to the samples.

A technique for the fabrication of various multiparametric porous silicon samples on a single substrate

Porous silicon (PSi) samples generally have a uniform thickness and pore size according to specific anodization conditions, as the Si wafer is entirely immersed into hydrofluoric (HF) acid during the anodization process. In contrast, multiparametric (MP) PSi, as described in the present work, is fabricated by inserting a Si wafer gradually (or by stages) into a HF solution during the anodization process. Consequently, MP-PSi allows single layer fabrication with a pore-size and layer thickness gradient or various multilayers, on a single substrate. Therefore, MP-PSi can be readily used in sensor application areas to determine optimized detection conditions for various materials, such as gas, liquid, and bio-materials. MP-PSi layer with a lateral pore gradient distribution can also be used as size-exclusion matrix. In addition, the MP-PSi multilayer array is expected to open up application areas involving optical electronic nose systems.