Detection Of Volatile Organic Compounds Research Articles

Visual Recognition of Volatile Organic Compounds by Photonic Nose Integrated with Multiple Metal-Organic Frameworks.

The photonic nose inspired by the olfactory system is an integrated detection platform constructed by multiple sensing units as channels. However, in the detection of volatile organic compounds (VOCs), the sensing results that cannot be directly readable and the poor ability to distinguish analytes with similar chemical properties are the main challenges faced by this sensor. Here, 8 metal-organic frameworks (MOF)-based photonic crystals are used as the basic sensing units to construct a photonic nose detection platform. The microscopic adsorption of VOCs by MOFs enables the photonic crystals (PCs) to produce macroscopic structural color output, and further makes the photonic nose have specific color fingerprints for different VOCs, the response time of all PCs to VOCs can be within 1s. Through the color fingerprint, the visual identification of VOCs produced by 5 common solvent vapors is realized, and 9 VOCs with similar chemical properties are further distinguished. In addition, the application potential of the photonic nose in the actual environment is verified by identifying different contents of benzene in the paint. It is envisaged that the MOF-based photonic nose has great reference value for the development of intelligent and multi-component synergistic functional gas sensors.

Self-cleaning SERS sensor based on flexible Ni3S2/MoS2@Ag@PDMS composites for label-free multiplex volatile organic compounds detection

Self-cleaning SERS sensor based on flexible Ni3S2/MoS2@Ag@PDMS composites for label-free multiplex volatile organic compounds detection

Review of Predator Emitted Volatile Organic Compounds and Their Potential for Predator Detection in New Zealand Forests

This review covers the volatile organic compounds (VOCs) emitted by the bodies and secretions of introduced mammalian predators in New Zealand forests, with a specific focus on mice, rats, ferrets, stoats, and possums. The primary aim is to compile information on these VOCs and assess the potential of exploiting these VOCs as unique biomarkers for predator detection in the forest. While a universal VOC has yet to be identified, the review discusses various VOCs associated with predators and their potential as unique biomarkers for detecting the presence of predators, including 2-heptanone, 4-heptanone, 2-octanone, and benzaldehyde. Furthermore, a brief overview of different VOC detection techniques is provided, connecting the selection of biosensing techniques with the detection of volatile biomarkers. Further research and advancement in the biosensing field hold substantial potential to enhance biomarker detection technologies and elevate predator management strategies within New Zealand forests.

Design and experiment of high-field asymmetric waveform ion mobility spectrometry chip based on an integrated temperature control printed circuit board structure.

During the detection of volatile organic compounds (VOC) using high-field asymmetric waveform ion mobility spectrometry (FAIMS), the ambient temperature significantly impacts the accuracy of planar FAIMS. To mitigate the influence of ambient temperature on detection accuracy and enhance resolution, a FAIMS system based on the inner impedance characteristics of a printed circuit board (PCB) was designed for temperature control. This study, conducted under standard atmospheric pressure, aimed to assess the signal stability of a planar FAIMS instrument with and without temperature control, and the effect of temperature change on the detection ability of acetone, ethanol, and their mixture was studied using PCB self-heating. Experimental results demonstrated that the base noise in FAIMS with temperature control was 0.2pA, whereas that in FAIMS without temperature control was 1.8pA. Notably, with increasing temperature, the detection ability of FAIMS changes accordingly. The optimal relative detection ability of acetone was observed when the electrode plate was heated to 45°C under an electric field of 15 kV/cm. This study provides a novel approach to improve the resolving power of FAIMS systems and their signal-to-noise ratio. The utilization of a PCB-based temperature control proved effective in stabilizing FAIMS signal characteristics and optimizing detection capabilities, particularly for VOCs such as acetone. These findings have significant implications for improving the accuracy and resolving power of FAIMS systems in VOC detection applications.

Artificial nose of scalable plasmonic array gas sensor for Multi-Dimensional SERS recognition of volatile organic compounds

Gas sensing is one kind of promising analytical technique for high-flux screening and evaluation. Volatile organic compounds (VOCs) analysis by surface-enhanced Raman spectroscopy (SERS) is arising but usually focuses on a single species of VOCs due to the limitations of complexity, stability, and accuracy in practical applications. Canine animals have a sensitive sense of smell due to their large number of olfactory cells. Inspired by this, here we innovatively integrate scalable plasmonic arrays and multi-dimensional chemometrics for simultaneous SERS detection of multiple food-borne VOCs. Both direct and indirect SERS strategies are integrated by coating the array surface with MOFs or different monolayers to provide multi-dimensional recognition and readouts. Four species of VOCs including bacterial metabolites, hydrogen sulfide, aldehyde, and biogenic amine were selectively captured and produced unique SERS spectral profiles. The multi-dimensional outputs greatly increase the dimensionality of VOC fingerprints, thereby significantly improving the sensitivity, reliability, and accuracy for freshness discrimination and forecasting in real food smell evaluation. By virtue of multi-dimensional SERS recognition and machine learning, the array gas sensor shows higher accuracy than traditional SERS analysis and is a promising platform for in situ, real-time, and high-flux gas sensing and inspection.

Ab initio investigation of functionalization of titanium carbide Ti3C2 MXenes to tune the selective detection of lung cancer biomarkers

Selected volatile organic compounds (VOCs), such as benzene (C6H6), cyclohexane (C6H12), isoprene (C5H8), cyclopropanone (C3H4O), propanol (C3H8O), and butyraldehyde butanal (C4H8O), in exhaled human breath can act as indicators or biomarkers of lung cancer diseases. Detection of such VOCs with low density would pave the way for an early diagnosis of the disease and thus early treatment and cure. In the present investigation, the density-functional theory (DFT) is applied to study the detection of the mentioned VOCs on Ti3C2TX MXenes, saturated with the functional groups Tx = O, F, S, and OH. For selectivity, comparative sensing of other interfering air molecules from exhaled breath, such as O2, N2, CO2, and H2O is further undertaken. Three functionalization (Tx = O, F, and S) are found promising for the selective detection of the studied VOCs, in particular Ti3C2O2 MXenes has shown distinct sensor response toward the C5H8, C6H6, C6H12, and C3H4O. The relatively strong physisorption (Eads≅-0.45to-0.65eV\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${E}_{ads}\\cong -0.45 to-0.65 {\ ext{eV}}$$\\end{document}), triggered between VOC and MXene due to an enhancement of van der Waals interaction, is found responsible to affect the near Fermi level states, which in turn controls the conductivity and consequently the sensor response. Meanwhile, such intermediate-strength interactions remain moderate to yield small desorption recovery time (of order τ≅μs-ms)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ au \\cong \\mu {\ ext{s}}-{\ ext{ms}})$$\\end{document} using visible light at room temperature. Thus, Ti3C2O2 MXenes are found promising candidate material for reusable biosensor for the early diagnosis of lung cancer diseases through the VOC detection in exhaled breath.

A Metal-Free Triazacoronene-Based Bimodal VOC Sensor.

Developing suitable sensors for selective and sensitive detection of volatile organic compounds (VOCs) is crucial for monitoring indoor and outdoor air quality. VOCs are very harmful to our health upon inhalation or contact. Bimodal sensor materials with more than one transduction capability (optical and electrical) offer the ability to extract complementary information from the individual analyte, thus improving detection accuracy and performance. The privilege of manipulating the optoelectronic properties of the polycyclic aromatic hydrocarbon-based semiconducting materials offers rapid signal transduction in multimodal sensing applications. A thiophene-functionalized triazacoronene (TTAC) donor-acceptor-donor (D-A-D) type sensor is reported here for VOC sensing. The single-crystal X-ray structure analysis of the TTAC revealed that a distinctive supramolecular polymer architecture was formed because of cooperative π-π and intermolecular D-A interactions and exhibited rapid signal transduction upon exposure to specific VOCs. The TTAC-embedded green luminescent paper-based test strip exhibited an on-off fluorescence response upon nitrobenzene vapor exposure for 120 s. The selective and rapid response is due to the fast photoinduced electron transfer, as is evident from the time-resolved excited-state dynamics and density functional theory studies. The thick-film-based prototype chemiresistive sensor detects harmful VOCs in a custom-made gas sensing system including benzene, toluene, and nitrobenzene. The TTAC sensor rapidly responds (200 s) at relatively low temperatures (180 οC) compared to other reported metal-oxide-based sensors.

Highly Sensitive and Selective Detection of Dimethyl Methyl Phosphonate with Copolymer‐Based QCM Sensors

AbstractIn this work, the volatile organic compounds (VOCs) sensing properties of a quartz crystal microbalance (QCM) transducer coated with six different poly(3‐methylthiophene) (P3MT) copolymerized with polypyrrole (PPy) are investigated. The sensor preparation involves the electrochemical deposition of P3MT, PPy, and P3MT‐co‐PPy on Au‐coated QCM transducers by electrochemical deposition techniques with a three‐electrode cell. The structural properties of the copolymer films are characterized using scanning electron microscopy, and their oxidation/reduction behavior is investigated through cyclic voltammetry. The copolymer‐based QCM sensors exhibit high sensitivity and selectivity to dimethyl methyl phosphonate and benzonitrile, even at low concentrations (<1 ppm) at room temperature. Langmuir, Freundlich, Temkin, and Dubinin–Radushkevich adsorption isotherms are studied to understand the VOCs sensing mechanism machine learning classification algorithms including quadratic discriminant (QD), neural nets, K‐nearest neighbors, linear discriminant, and support vector machines are applied to classify the sensor responses for the 12 different analytes. With the help of machine learning algorithms, tested analytes are successfully classified into their groups. The highest accuracy of 97.34% is achieved using the QD method. The developed sensor, combined with machine learning algorithms, shows promising potential for accurate and reliable detection and classification of VOCs.

Development of Multichannel Quartz Tuning Fork Sensor Array System for the Detection of Volatile Organic Compounds

Development of Multichannel Quartz Tuning Fork Sensor Array System for the Detection of Volatile Organic Compounds

Graphene and metal-organic framework hybrids for high-performance sensors for lung cancer biomarker detection supported by machine learning augmentation.

Conventional diagnostic methods for lung cancer, based on breath analysis using gas chromatography and mass spectrometry, have limitations for fast screening due to their limited availability, operational complexity, and high cost. As potential replacement, among several low-cost and portable methods, chemoresistive sensors for the detection of volatile organic compounds (VOCs) that represent biomarkers of lung cancer were explored as promising solutions, which unfortunately still face challenges. To address the key problems of these sensors, such as low sensitivity, high response time, and poor selectivity, this study presents the design of new chemoresistive sensors based on hybridised porous zeolitic imidazolate (ZIF-8) based metal-organic frameworks (MOFs) and laser-scribed graphene (LSG) structures, inspired by the architecture of the human lung. The sensing performance of the fabricated ZIF-8@LSG hybrid sensors was characterised using four dominant VOC biomarkers, including acetone, ethanol, methanol, and formaldehyde, which are identified as metabolomic signatures in lung cancer patients' exhaled breath. The results using simulated breath samples showed that the sensors exhibited excellent performance for a set of these biomarkers, including fast response (2-3 seconds), a wide detection range (0.8 ppm to 50 ppm), a low detection limit (0.8 ppm), and high selectivity, all obtained at room temperature. Intelligent machine learning (ML) recognition using the multilayer perceptron (MLP)-based classification algorithm was further employed to enhance the capability of these sensors, achieving an exceptional accuracy (approximately 96.5%) for the four targeted VOCs over the tested range (0.8-10 ppm). The developed hybridised nanomaterials, combined with the ML methodology, showcase robust identification of lung cancer biomarkers in simulated breath samples containing multiple biomarkers and a promising solution for their further improvements toward practical applications.

Optimizing the piezoresistive design on the microcantilever for enhancing stress sensing and temperature effects

This paper addresses the issue of volatile organic compounds (VOCs), hazardous materials commonly present in paints, perfumes, petroleum and oil refineries, and plastic products, which can lead to health hazards. The detection of these toxic compounds has been a compelling subject for researchers. In this study, a novel approach is presented, involving the design of a sensor for VOC determination using a piezoresistive microcantilever. Microcantilevers have gained significant attention in electrochemical applications due to their enhanced sensitivity. The research explores various design factors, such as length, thickness, and material selection, to optimize the sensor’s response. Specifically, reducing the cantilever’s thickness is considered to improve the deflection sensitivity. To enhance the sensitivity of the piezoresistive sensor, particular emphasis is placed on developing the piezoresistive sensing layer to effectively address stress-induced changes. Experimental investigations involve exploring different cantilever shapes and piezolayer configurations to achieve the desired optimized condition. Ultimately, the rectangular cantilever shape is reshaped into a U-shape, which demonstrates enhanced sensitivity, offering promising possibilities for VOC detection. This study presents valuable insights into the design and optimization of piezoresistive microcantilever sensors for efficient VOC detection, its temperature effects, and monitoring applications.

Detection of medically relevant volatile organic compounds with graphene field-effect transistors and separated by low-frequency spectral and time signatures.

Exhaled human breath contains a mixture of gases including nitrogen, oxygen, carbon dioxide, water vapour and low molecular weight volatile organic compounds (VOCs). Different VOCs detected in human breath condensate have been recently related to several metabolic processes occurring inside body tissues in the pathological state, as candidate biomarkers for monitoring conditions such as lung injury, airway inflammation, immunity dysfunction, infection, and cancer. Current techniques for detecting these compounds include several types of mass spectroscopy, which are highly costly, time-consuming and dependent on trained personnel for sample analysis. The need for fast and label-free biosensors is paving the way towards the design of novel and portable electronic devices for point-of-care diagnosis with VOCs such as E-noses, and based on the measurement of signal signatures derived from their chemical composition. In this paper, we propose a device for VOC detection that was tested inside a controlled gas flow setup, resorting to graphene field-effect transistors (GFETs). Electrical measurements from graphene directly exposed to nitrogen plus VOC vapours involved cyclic measurements for the variation of graphene's resistance and low-frequency spectral noise in order to obtain distinctive signatures of the tested compounds in the time and frequency domains related, respectively, to Gutmann's theory for donor-acceptor chemical species and spectral sub-band analysis.

Identification of acetaldehyde based on plasmonic patterns of a gold nanostructure conjugated with chromophore and H2O2: a new platform for the rapid and low-cost analysis of carcinogenic agents by colorimetric affordable test strip (CATS).

Acetaldehyde, a prevalent carbonyl compound in fermented foods, poses challenges in various applications due to its reactivity. This study addresses the need for efficient acetaldehyde detection methods across biotechnological, environmental, pharmaceutical, and food sectors. Herein, we present a novel colorimetric/UV spectrophotometric approach utilizing gold nanoparticles (AuNPs), particularly gold nano-flowers (AuNFs), for sensitive acetaldehyde identification. The method exhibits a notable sensitivity, detecting acetaldehyde at concentrations as low as 0.1 μM. The mechanism involves the interaction of acetaldehyde molecules with AuNFs, leading to a significant change in the absorbance spectrum, which serves as the basis for detection. Moreover, its applicability extends to human biofluids, notably urine samples. Integration with a cost-effective one-drop microfluidic colorimetric device (OD-μPCD) enables the development of an affordable test strip (CATS). This semi-analytical device, employing a multichannel OD-μPCD, facilitates real-time analysis of acetaldehyde in human samples. Our findings demonstrate the pioneering utilization of AuNPs for selective and sensitive acetaldehyde detection, promising advancements in environmental and occupational safety standards, and laying a foundation for enhanced detection and monitoring of related volatile organic compounds (VOCs).

Organohalogenochromism (OHC) of D–π–A pyridinium dye polymer films and the colorimetric detection of volatile organic halogen compounds

We propose that polymeric organohalogenochromic dyes are one of the most promising and convenient functional materials for the colorimetric detection of volatile organohalogen compounds (VOHCs), including CH2Cl2 and CHCl3.

Efficient detection of specific volatile organic compounds associated with COVID-19 using CrX2 (X = Se, Te) monolayers

Motivated by the necessity of efficient detection of COVID-19 through specific biomarkers, such as ethyl butyrate and heptanal, we performed first principles calculations based on density functional theory (DFT) to explore the sensing mechanism of pure, vacancy-induced, and single atom catalyzed CrX2 (X = Se, Te) monolayers. Both the biomarkers barely bind on pristine CrSe2. However with Se-vacancy (As-doping) suitable adsorption energies of −1.44 (−0.70), and −0.70 (−0.54) eV were obtained for ethyl butyrate and heptanal, respectively. Te-vacancy (Sn-doping) in CrTe2 resulted in much stronger binding of ethyl butyrate and heptanal with the adsorption energies of −2.04 (−2.40), and −2.90 (−2.40) eV, respectively. The adsorption of the mentioned biomarkers altered the magnetic and electronic properties of defected CrX2, which were explored through spin-polarized density of states, electrostatic potential and work function calculations. Measurable changes in electronic and magnetic properties confirmed excellent sensing potential of CrX2. Statistical thermodynamics analysis based on Langmuir adsorption model was employed to study the sensing of the biomarkers at different temperature and pressure ranges for real-world application.

Unravelling the sensing efficacy of graphene oxide towards hazardous volatile organic compounds in the polyurethane industry

Graphene oxide (GO) sensors comprising of a computationally modelled hexahydroxyl ring system exhibit exceptional selectivity towards detection of hazardous volatile organic compounds (VOCs) emitted from polyurethane industries.

Qualitative and quantitative rapid detection of VOCs differentially released by VAP-associated bacteria using PTR-MS and FGC-PTR-MS.

Ventilator-associated pneumonia (VAP) is a prevalent disease caused by microbial infection, resulting in significant morbidity and mortality within the intensive care unit (ICU). The rapid and accurate identification of pathogenic bacteria causing VAP can assist clinicians in formulating timely treatment plans. In this study, we attempted to differentiate bacterial species in VAP by utilizing the volatile organic compounds (VOCs) released by pathogens. We cultured 6 common bacteria in VAP in vitro, including Acinetobacter baumannii, Enterobacter cloacae, Escherichia coli, Pseudomonas aeruginosa, Stenotrophomonas maltophilia, and Staphylococcus aureus, which covered most cases of VAP infection in clinic. After the VOCs released by bacteria were collected in sampling bags, they were quantitatively detected by a proton transfer reaction-mass spectrometry (PTR-MS), and the characteristic ions were qualitatively analyzed through a fast gas chromatography-proton transfer reaction-mass spectrometry (FGC-PTR-MS). After conducting principal component analysis (PCA) and analysis of similarities (ANOSIM), we discovered that the VOCs released by 6 bacteria exhibited differentiation following 3 h of quantitative cultivation in vitro. Additionally, we further investigated the variations in the types and concentrations of bacterial VOCs. The results showed that by utilizing the differences in types of VOCs, 6 bacteria could be classified into 5 sets, except for A. baumannii and E. cloacae which were indistinguishable. Furthermore, we observed significant variations in the concentration ratio of acetaldehyde and methyl mercaptan released by A. baumannii and E. cloacae. In conclusion, the VOCs released by bacteria could effectively differentiate the 6 pathogens commonly associated with VAP, which was expected to assist doctors in formulating treatment plans in time and improve the survival rate of patients.

Development of a portable gas chromatography linear ion trap mass spectrometer (GC-LIT-MS) for VOCs analysis in water

The detection of volatile organic compounds (VOCs) in water faces challenges due to the presence of complex matrix interferences and low concentration. This paper presented a portable gas chromatography linear ion trap mass spectrometer (GC-LIT-MS) coupled with dynamic headspace sampling (DHS) system for sensitive and rapid on-site analysis of VOCs in water. The instrument weighs 18 kg and has compact dimensions of 43 cm × 35 cm x 20 cm, offering portability and convenience. A low thermal mass (LTM) chromatographic column, utilizing resistive heating, enables rapid heating and cooling within the runtime of GC. The linear ion trap, for the first time, has been integrated as a mass analyser in portable gas chromatography-mass spectrometer (GC-MS). Its ability to store a greater number of ions within the trap expands the dynamic range of the instrument. The influence of dynamic headspace injection conditions on the purging efficiency of VOCs was investigated and the equilibrium temperature was optimized. The GC-LIT-MS method was demonstrated to be capable to identify and separate 55 VOCs in water within 4 min, with most of them exhibiting detection limits of less than 1 μg L−1. The calibration of 4 VOCs with concentrations ranged from 2 parts per million (ppm) to 200 ppm showed excellent linearity (R2 > 0.99) and dynamic range more than five orders of magnitude. Resolution superior to unit mass was achieved within the range of 15 AMU to 550 AMU.

Cataluminescence sensor based on LaCO3OH microspheres for volatile organic compounds detection and pattern recognition

The cataluminescence (CTL) reaction detects the presence and concentration of toxic volatile organic compounds by detecting the luminescence intensity of the different components of the gas mixture. In our study, a cataluminescence online sensor system based on LaCO3OH microspheres was developed for the low concentration detection of volatile organic compounds. Multi-dimensional CTL test was carried out to analyse the correlation characteristics of heterogeneous analytes among the catalytic activity, selectivity, sensitivity, response/recover time, stability, and photoelectric signals by changing the parameters of wavelength, flow rate, temperature, and response time under the optimal conditions (280 mL/min, 180ºC, and 480 nm). Due to noise interference received by the CTL signal, the weak CTL signal was filtered based on the time-frequency characteristics of the CTL pattern signal power frequency interference and background noise. Next, this study also studied the mechanism action of the cataluminescence sensor based on LaCO3OH microspheres for gas detection, including ethyl ether, acetone, chloroform, and formaldehyde. The principal component analysis (PCA) algorithm was adopted to analyse the CTL patterns, after threshold filtering, the total variance was improved from 89.23% to 98.78% and each vapour gave its unique CTL patterns. Moreover, clustering and identification are discussed to analyse the results, including Hierarchical Cluster Analysis (HCA) and Radial Basis Function Neural Networks (RBFNN), was also discussed. The excellent cluster and recognition ability indicate the feasibility of this CTL sensor for volatile compound determination.

Tunable multimode emission induced by charge transfer and multiple resonance effect

Single-component luminescent materials with dual emission properties show great promise in material and life science. Here, we report a novel thermally activated delayed fluorescence (TADF) emitter BO-PST based on a rigid B-embedded dioxygen-bridged acceptor (A) and flexible phenothiazine donor (D). The flexibility of D unit contributes to different charge transfer characteristic and interesting multimode emission in various environment, including D-A-type TADF emission, multi-resonant (MR) fluorescence emission and MR induced afterglow with long lifetime of 1.55 s. Single-crystal structures and theoretical calculations prove that dual emission originates from the quasi-equatorial and quasi-axial conformers of the phenothiazine unit, respectively. The dynamic multicolor properties demonstrate the potential of the novel BO-PST molecule in the volatile organic compounds (VOCs) detection and the stimulus-responsive application.