Volatile Organic Compounds Sensor Research Articles

Demonstration of VOC Fenceline Sensors and Canister Grab Sampling near Chemical Facilities in Louisville, Kentucky.

Experimental fenceline sensor pods (SPods) fitted with 30 s duration canister grab sampling (CGS) systems were deployed at a site near chemical facilities in Louisville, KY, from 4 June 2018 to 5 January 2020. The objective of the study was to better understand lower cost 10.6 eV photoionization detector (PID)-based volatile organic compound (VOC) sensors and investigate their utility for near-source emissions detection applications. Prototype SPods containing PID sensor elements from two different manufacturers yielded between 78% and 86% valid data over the study, producing a dataset of over 120,000 collocated pair fenceline measurements averaged into 5-min datapoints. Ten-second time-resolved SPod data from an elevated fenceline sensor signal day are presented, illustrating source emission detections from the direction of a facility 500 m west of the monitoring site. An SPod-triggered CGS acquired in the emission plume on this day contained elevated concentrations of 1,3-butadiene and cyclohexane (36 parts per billion by volume (ppbv) and 637 ppbv, respectively), compounds known to be emitted by this facility. Elevated concentrations of these compounds were observed in a subset of the 61 manual and triggered CGS grab samples acquired during the study, with winds from the west. Using novel wind-resolved visualization and normalization approaches described herein, the collocated pair SPod datasets exhibited similarity in emission source signature. With winds from the west, approximately 50% of SPod readings were above our defined theoretical detection limit indicating persistent measurable VOC signal at this site. Overall, this 19-month study demonstrated reasonable prototype SPod operational performance indicating that improved commercial forms of lower cost PID sensors could be useful for select VOC fenceline monitoring applications.

Field Test of Mini Photoionization Detector-Based Sensors—Monitoring of Volatile Organic Pollutants in Ambient Air

The determination of the concentrations of the organic compounds in ambient air using reference methods is a time-consuming process. The samples must be collected on a specific sorbent material and analyzed. In the best-case scenario, the analysis may be performed on site by portable chromatography techniques; otherwise, transport and laboratory analysis is necessary. Continuous sensory measurement is advantageous, especially concerning speed, resolution, price and ease of use. On the other hand, questions are raised, especially on the subject of the quality of data obtained by sensory measurements. The authors tested several types of volatile organic compound (VOC) sensors. The chosen type was deployed in a 25-unit sensor network for further testing by parallel measurements with the reference technique within the CLAIRO project.

Medical Diagnosis Using Volatile Organic Compounds Sensors

Volatile organic compounds (VOCs) are important biomarkers in exhaled breath or skin secretion of patients under various medical or pre-medical conditions. As such, VOCs have been explored as alternative biomarkers in the detection of diseases, including asthma, tuberculosis, and lung cancer. In this regard, a rapid, cost-effective, facile, and sample-free strategy is advantageous and critically needed for premedical screening, medical diagnosis, and health monitoring. In this review, we present an overview of the latest progress of using nanomaterial-based chemo-resistive VOC sensors for fast, real-time, and non-invasive diagnosis of diseases via detecting VOCs from exhaled breath and other sources from human body. The origin and emission of VOCs are summarized from human body, and the VOC signatures are discussed as related to specific disease. Targeting specific VOCs, chemoresistive sensors using different nanomaterials are reviewed in terms of their sensing performance metrics including sensitivity, selectivity, response/recovery time, and stability. Various strategies for improving VOC sensor performance are discussed, specifically on the material and signal processing-based approaches.

Metal oxide thin films coated evanescent wave based fiber optic VOC sensor

Recently, there has been an increase in the demand for sensor devices that monitor the concentration of volatile organic compounds (VOC) for disease severity prognosis. This paper reports an experimental analysis of evanescent wave-based fiber optic VOC sensor utilizing clad modification technique. Zinc oxide (ZnO), aluminum-doped zinc oxide (AZO), and tin oxide (SnO2) thin films are individually deposited over the unclad portion of the optical fiber using Radiofrequency (RF) magnetron sputtering. The deposited metal oxide thin films were characterized using the Scanning Electron Microscope (SEM), Energy dispersive spectroscopy (EDS), X-ray diffraction (XRD), Ultraviolet-visible (UV-Vis) spectroscopy, and Ellipsometer device. Spectral characteristics of all three sensor probes were tested for different VOCs: acetone, acetophenone, ethanol, and isopropanol (IPA), with concentrations varying from 0 to 250 ppm. Among them, SnO2 coated sensor probe shows the maximum sensor response of 21.2% towards 250 ppm IPA, with a response and recovery times of ~17 and ~21 s, respectively. In addition to the intensity variation, the prepared sensor probes also exhibit the wavelength shift due to the lossy mode resonance phenomenon. Specifically, SnO2 coated sensor probe shows a maximum wavelength shift of 2.4% towards 250 ppm IPA. The detection limit of the SnO2 coated sensor probe was observed to be 300 ppb.

Smart-Autonomous Wireless Volatile Organic Compounds Sensor Node for Indoor Air Quality Monitoring Application.

Several studies reported the significant effect of indoor air quality on human health, safety, productivity, and comfort because most humans usually conduct 80%–90% of their activity inside the building. This is generally due to the fact that indoor pollution is associated with volatile organic compounds (VOCs), pollutants with chronic health effects, both non-carcinogenic and carcinogenic, on humans. Therefore, this study focused on developing wireless VOCs sensor nodes with a low-power strategy feature to perform an autonomous operation in indoor air quality monitoring (IAQM). The sensor node mainboard consists of a microcontroller-based AVR (ATmega-4808) that supports a low power mode and low-power IAQ-Core sensor for VOCs detection. The low-power sensing algorithm developed also allowed the sensor node to consume a total power of 0.22 mAh for one cycle of operation, which includes the initial process, TVOCs value reading process, data transmitting process, and low power mode process at a time interval of 30 min. The most significant power was observed to be consumed in the data transmitting process with 0.13 mAh or 58% of total power consumption in one cycle of sensor node operation. Furthermore, the 10F capacitance of the supercapacitor was able to drive the VOCs sensor node for 139 s and it was recommended that further studies use micro energy harvesting (from an indoor environment) to extend its lifetime. The 1541-minute field experiment conducted also showed that TVOCs and CO2 values were successfully measured and displayed over an internet connection on the monitoring terminal dashboard. The recorded real-time TVOCs value of 175 ppb (<200 ppb) indicates good air quality.

Flory-Huggins VOC Photonics Sensor Made of Cellulose Derivatives.

As a widespread air pollutant, volatile organic compounds (VOCs) are harmful to the human body's skin, nervous system, and respiratory system. Low-cost, extensive, and continuous detection of VOCs is of great significance to human health. We infiltrated and coated cellulose acetate on the inverse opal photonic crystal skeleton of methylcellulose-polyvinyl alcohol-graphene oxide to construct a degradable, high-toughness cellulose VOC sensor. Cellulose acetate enhances the response to VOCs and achieves a highly selective response to acetone vapor due to the smaller Flory-Huggins parameter with acetone. This work proposes a general, simple, easy-to-use, and highly selective photonic crystal VOC sensor development strategy. Calculated from the Flory-Huggins solution theory, a suitable polymer was selected to modify the inverse opal photonic crystal framework and achieve high selectivity detection.

Construction of Large-Scale Conjugated Functionalized Cyclotriphosphazene Lanthanide Framework for Selective Sensing of Volatile Organic Compounds and Assembly of Color-Tunable Dye-Encapsulated Composites.

A flexible functionalized cyclotriphosphazene hexacarboxylic acid, hexakis(4-carboxylatephenoxy) cyclotriphosphazene (HCPCP), is used for the synthesis of a family of fluorescent Ln-HCPCP frameworks (Ln = La, Pr, Nd, Gd, and Ho). Structural analysis shows that the compounds exhibit 3D structures with [Ln3(COO)10], secondary building units formed by Ln-O-C-O-Ln connection. Then the molecules are connected to each other through HCPCP, forming rectangular channels along the c-direction. Interestingly, the fluorescence sensing studies show that compound 1 could be used as a multifunctional fluorescence sensor toward volatile organic compounds via different fluorescence emission behaviors. Moreover, a series of Dye@La-HCPCP composites (Dye = rhodamine B, safranine T, crystal violet, and malachite green) are successfully prepared with different quantum yields by the solvothermal reaction followed by cation exchanges.

Breath Sensor Technology for the Use in Mechanical Lung Ventilation Equipment for Monitoring Critically Ill Patients.

Background: The need for mechanical lung ventilation is common in critically ill patients, either with COVID-19 infection or due to other causes. Monitoring of patients being ventilated is essential for timely and improved management. We here propose the use of a novel breath volatile organic compound sensor technology to be used in a mechanical lung ventilation machine for this purpose; the technology was evaluated in critically ill COVID-19 patients on mechanical lung ventilation. Methods: Based on the consistency results of our study data, the breath sensor device with metal oxide gas sensors and environment-controlling sensors was mounted on the ventilation exhaust port of the ventilation machine; this allowed to ensure additional safety since the device was placed outside the contour between the patient and equipment. Results: The sensors allowed stable registration of the signals for up to several weeks for 10 patients in total, depending on the storage amount; a proportion of patients were intubated or received tracheostoma during the evaluation period. Future studies are on the way to correlate sensor readings to other parameters characterizing the severity of the patient condition and outcome. Conclusions: We suppose that such technology will allow patient monitoring in real-time for timely identification of deterioration, potentially requiring some change of management. The obtained results are preliminary and further studies are needed to examine their clinical significance.

Polymer Microtip on a Multimode Optical Fiber as a Threshold Volatile Organic Compounds Sensor.

Polymer microtips are 3D microstructures manufactured on the end face of an optical fiber by using the photopolymerization process. Such micro-optic elements made on a multi-mode optical fiber were previously tested as a transducer of refractive index sensor. These studies were an inspiration to investigate the possibility of using this type of transducer to measure the presence of volatile organic compounds in the air. The experimental results of microtips polymerized with UV and VIS were reported. It was possible to detect the presence of five different volatile compounds in the air due to the sensitivity of the transducer to the refractive indices changes. These changes were induced by the vapors condensed on the microtip surface. The measured time responses have shown that the return loss decreases rapidly as the microtip is inserted inside a glass vial filled with the tested compound. Moreover, correlations between calculated dynamic ranges and refractive indices and volumes of the volatile compounds inside the vials were negligible. Therefore, this type of sensor can be categorized as a condensed material threshold sensor. This sensor can be used in warning systems for monitoring leakages of pipelines carrying volatile chemicals.

Nanoporous Fluorescent Microresonators for Non-wired Sensing of Volatile Organic Compounds down to the ppb Level

Nanoporous Fluorescent Microresonators for Non-wired Sensing of Volatile Organic Compounds down to the ppb Level

Paving the Way for a Green Transition in the Design of Sensors and Biosensors for the Detection of Volatile Organic Compounds (VOCs).

The efficient and selective detection of volatile organic compounds (VOCs) provides key information for various purposes ranging from the toxicological analysis of indoor/outdoor environments to the diagnosis of diseases or to the investigation of biological processes. In the last decade, different sensors and biosensors providing reliable, rapid, and economic responses in the detection of VOCs have been successfully conceived and applied in numerous practical cases; however, the global necessity of a sustainable development, has driven the design of devices for the detection of VOCs to greener methods. In this review, the most recent and innovative VOC sensors and biosensors with sustainable features are presented. The sensors are grouped into three of the main industrial sectors of daily life, including environmental analysis, highly important for toxicity issues, food packaging tools, especially aimed at avoiding the spoilage of meat and fish, and the diagnosis of diseases, crucial for the early detection of relevant pathological conditions such as cancer and diabetes. The research outcomes presented in the review underly the necessity of preparing sensors with higher efficiency, lower detection limits, improved selectivity, and enhanced sustainable characteristics to fully address the sustainable manufacturing of VOC sensors and biosensors.

Tackling Humidity with Designer Ionic Liquid-Based Gas Sensing Soft Materials.

Relative humidity is simultaneously a sensing target and a contaminant in gas and volatile organic compound (VOC) sensing systems, where strategies to control humidity interference are required. An unmet challenge is the creation of gas-sensitive materials where the response to humidity is controlled by the material itself. Here, humidity effects are controlled through the design of gelatin formulations in ionic liquids without and with liquid crystals as electrical and optical sensors, respectively. In this design, the anions [DCA]− and [Cl]− of room temperature ionic liquids from the 1-butyl-3-methylimidazolium family tailor the response to humidity and, subsequently, sensing of VOCs in dry and humid conditions. Due to the combined effect of the materials formulations and sensing mechanisms, changing the anion from [DCA]− to the much more hygroscopic [Cl]−, leads to stronger electrical responses and much weaker optical responses to humidity. Thus, either humidity sensors or humidity-tolerant VOC sensors that do not require sample preconditioning or signal processing to correct humidity impact are obtained. With the wide spread of 3D- and 4D-printing and intelligent devices, the monitoring and tuning of humidity in sustainable biobased materials offers excellent opportunities in e-nose sensing arrays and wearable devices compatible with operation at room conditions.

Towards a multisensor station for automated biodiversity monitoring

Rapid changes of the biosphere observed in recent years are caused by both small and large scale drivers, like shifts in temperature, transformations in land-use, or changes in the energy budget of systems. While the latter processes are easily quantifiable, documentation of the loss of biodiversity and community structure is more difficult. Changes in organismal abundance and diversity are barely documented. Censuses of species are usually fragmentary and inferred by often spatially, temporally and ecologically unsatisfactory simple species lists for individual study sites. Thus, detrimental global processes and their drivers often remain unrevealed. A major impediment to monitoring species diversity is the lack of human taxonomic expertise that is implicitly required for large-scale and fine-grained assessments. Another is the large amount of personnel and associated costs needed to cover large scales, or the inaccessibility of remote but nonetheless affected areas.To overcome these limitations we propose a network of Automated Multisensor stations for Monitoring of species Diversity (AMMODs) to pave the way for a new generation of biodiversity assessment centers. This network combines cutting-edge technologies with biodiversity informatics and expert systems that conserve expert knowledge. Each AMMOD station combines autonomous samplers for insects, pollen and spores, audio recorders for vocalizing animals, sensors for volatile organic compounds emitted by plants (pVOCs) and camera traps for mammals and small invertebrates. AMMODs are largely self-containing and have the ability to pre-process data (e.g. for noise filtering) prior to transmission to receiver stations for storage, integration and analyses. Installation on sites that are difficult to access require a sophisticated and challenging system design with optimum balance between power requirements, bandwidth for data transmission, required service, and operation under all environmental conditions for years. An important prerequisite for automated species identification are databases of DNA barcodes, animal sounds, for pVOCs, and images used as training data for automated species identification. AMMOD stations thus become a key component to advance the field of biodiversity monitoring for research and policy by delivering biodiversity data at an unprecedented spatial and temporal resolution.

Progress in development of metal organic frameworks for electrochemical sensing of volatile organic compounds

Organic compounds threaten human health and the environment, and hence their detection is perilous for human safety and environment protection. Metal-organic frameworks (MOFs) are the three-dimensional hybrid porous materials with large surface area, tunability and good stability. Different MOFs based instrumental and material-based approaches have been developed in this line to research and expand the knowledge of MOFs as sensing platforms for a variety of organic molecules. MOFs having π-extended aromatic structures can be exploited in electroanalytical approach and thus pose lower detection limits in sensitive and selective detection of organic moieties. The present review will focus onto the categorization of different volatile organic compounds (VOCs) along with the recent progress in the development of MOF-based electrochemical sensors for volatile organic compounds. This review will pave a way to design more MOF based electrochemical sensors with excellent analytical response.

Engineering of metal-organic framework nanomaterials on long-period fiber grating for acetone vapor sensing.

Metal-organic framework (MOF) material is one of the most promising porous nanomaterials for volatile organic compound (VOC) adsorption and sensing. The large surface area and the high porosity of MOF contribute to the high sensitivity of MOF-based VOC sensors. In this study, we engineer the coating of the zeolitic imidazolate framework material ZIF-8 grown on the surface of a long-period fiber grating (LPFG) for acetone vapor sensing. Being a periodic structure formed in a single-mode optical fiber, an LPFG is designed to couple light from the core to the cladding of the fiber at a specific resonance wavelength. Adsorption of acetone vapor molecules in the framework of the ZIF-8 coating can change the refractive index of the coating and cause a shift in the resonance wavelength of the LPFG. The sensitivity of the resonance shift of the LPFG to the acetone vapor concentration depends strongly on the thickness of the ZIF-8 coating. To create a dense ZIF-8 coating, at least five growth cycles of ZIF-8 (30 min growth for one cycle) are required, and nine growth cycles can create a 500 nm thick coating. The LPFG coated with nine growth cycles of ZIF-8 provides a high sensitivity of 21.9 nm ppm-1, a low detection limit of 1.4 ppm, and a wide detection range of about 1500 ppm. Our results can facilitate the development of high-performance optical fiber sensors based on MOF for VOC detection.

Selective Detection of Volatile Organics in a Mixture Using a Photoionization Detector and Thermal Desorption from a Nanoporous Preconcentrator.

The selective detection of individual hazardous volatile organic compounds (VOCs) within a mixture is of great importance in industrial contexts due to environmental and health concerns. Achieving this with inexpensive, portable detectors continues to be a significant challenge. Here, a novel thermal separator system coupled with a photoionization detector has been developed, and its ability to selectively detect the VOCs isopropanol and 1-octene from a mixture of the two has been studied. The system includes a nanoporous silica preconcentrator in conjunction with a commercially available photoionization detector (PID). The PID is a broadband total VOC sensor with little selectivity; however, when used in conjunction with our thermal desorption approach, selective VOC detection within a mixture can be achieved. VOCs are adsorbed in the nanoporous silica over a 5 min period at 5 °C before being desorbed by heating at a fixed rate to 70 °C and detected by the PID. Different VOCs desorb at different times/temperatures, and mathematical analysis of the set of PID responses over time enabled the contributions from isopropanol and 1-octene to be separated. The concentrations of each compound individually could be measured in a mixture with limits of detection less than 10 ppbv and linearity errors less than 1%. Demonstration of a separation of a mixture of chemically similar compounds, benzene and o-xylene, is also provided.

Flexible Impedimetric Electronic Nose for High-Accurate Determination of Individual Volatile Organic Compounds by Tuning the Graphene Sensitive Properties

We investigated functionalized graphene materials to create highly sensitive sensors for volatile organic compounds (VOCs) such as formaldehyde, methanol, ethanol, acetone, and isopropanol. First, we prepared VOC-sensitive films consisting of mechanically exfoliated graphene (eG) and chemical graphene oxide (GO), which have different concentrations of structural defects. We deposited the films on silver interdigitated electrodes on Kapton substrate and submitted them to thermal treatment. Next, we measured the sensitive properties of the resulting sensors towards specific VOCs by impedance spectroscopy. We obtained the eG- and GO-based electronic nose composed of two eG films- and four GO film-based sensors with variable sensitivity to individual VOCs. The smallest relative change in impedance was 5% for the sensor based on eG film annealed at 180 °C toward 10 ppm formaldehyde, whereas the highest relative change was 257% for the sensor based on two-layers deposited GO film annealed at 200 °C toward 80 ppm ethanol. At 10 ppm VOC, the GO film-based sensors were sensitive enough to distinguish between individual VOCs, which implied excellent selectivity, as confirmed by Principle Component Analysis (PCA). According to a PCA-Support Vector Machine-based signal processing method, the electronic nose provided identification accuracy of 100% for individual VOCs. The proposed electronic nose can be used to detect multiple VOCs selectively because each sensor is sensitive to VOCs and has significant cross-selectivity to others.

Development and Fabrication of Carbon Nanotube (CNT)/CuO Nanocomposite for Volatile Organic Compounds (VOCs) Gas Sensor Application

AbstractVolatile organic compounds (VOCs) have been recognized as one of the primary trace segments of atmospheric air pollutants. The change in the level of VOCs in the surrounding environment can lead to chronic health issues, respiratory problems, nerve system disorder, and toxicity in kidneys/liver. Thus, monitoring of VOCs concentration in the surrounding environment is significant for avoiding serious health problems. Herein, copper oxide (CuO) nanoparticle and carbon nanotube (CNT) nanocomposite (NC) are presented for the efficient detection of VOCs. The scalable sol‐gel method is adopted for the controlled growth of CNT/CuO NC. The structural, elemental, and morphological analysis is performed by XRD, FTIR spectroscopy, and SEM characterization, respectively. The VOCs sensor was fabricated by drop‐casting the as‐synthesized CNT/CuO NC on interdigitated electrodes (IDEs). The CNT/CuO sensing response is analyzed for six VOCs that include toluene, methanol, acetone, chloroform, xylene, and benzene. The CNT/CuO response towards different VOCs is investigated with respect to change in resistance of the material in the presence of test VOC and in an inert atmosphere. In comparison to other VOCs, the sensor exhibits high sensitivity toward benzene. The estimated change in relative resistance (AR) for benzene is ≈0.62% for 500 ppm concentration. Moreover, the sensor apprehended a detection of benzene with a concentration as low as 5 ppm. The as‐synthesized CNT/CuO NC offers high sensitivity and low detection limit, which benchmark its potential for benzene detection.

Reduced Graphene Oxide-Metalloporphyrin Sensors for Human Breath Screening

The objective of this study is to validate reduced graphene oxide (RGO)-based volatile organic compounds (VOC) sensors, assembled by simple and low-cost manufacturing, for the detection of disease-related VOCs in human breath using machine learning (ML) algorithms. RGO films were functionalized by four different metalloporphryins to assemble cross-sensitive chemiresistive sensors with different sensing properties. This work demonstrated how different ML algorithms affect the discrimination capabilities of RGO–based VOC sensors. In addition, an ML-based disease classifier was derived to discriminate healthy vs. unhealthy individuals based on breath sample data. The results show that our ML models could predict the presence of disease-related VOC compounds of interest with a minimum accuracy and F1-score of 91.7% and 83.3%, respectively, and discriminate chronic kidney disease breath with a high accuracy, 91.7%.

Quantitative volatile organic compound sensing with liquid crystal core fibers

SummaryPolymer fibers with liquid crystals (LCs) in the core have potential as autonomous sensors of airborne volatile organic compounds (VOCs), with a high surface-to-volume ratio enabling fast and sensitive response and an attractive non-woven textile form factor. We demonstrate their ability to continuously and quantitatively measure the concentration of toluene, cyclohexane, and isopropanol as representative VOCs, via the impact of each VOC on the LC birefringence. The response is fully reversible and repeatable over several cycles, the response time can be as low as seconds, and high sensitivity is achieved when the operating temperature is near the LC-isotropic transition temperature. We propose that a broad operating temperature range can be realized by combining fibers with different LC mixtures, yielding autonomous VOC sensors suitable for integration in apparel or in furniture that can compete with existing consumer-grade electronic VOC sensors in terms of sensitivity and response speed.