Vapor Recognition Research Articles

AIE-active light up probe for sensitive detection of amine vapors and its practical application in food spoilage monitoring

Amines act as a crucial role in agricultural field, chemical and food industries, but volatile amine vapor will cause environmental pollution and threat to human health. Thus, design and development of probes for amine vapor detection possesses great application potential. However, some already existing fluorescent probes for amine vapor detection generally exist some defects, such as easily suffering from aggregation caused emission quenching (ACQ) effect. In this work, a simple fluorescent sensor DEMCA-PA for light-up detection of amine vapor was successfully constructed, and DEMCA-OH produced via DEMCA-PA interacting with ammonia displayed remarkable aggregation-induced emission (AIE) properties. Thus, a portable probe for amine vapor recognition was constructed via depositing DEMCA-PA on filter paper, this probe has good selectivity, fast response time, high sensitivity, and lower detection limit (7.9 ppm), the mechanism was further confirmed by DFT calculations and UV-spectra property and HPLC analysis. Given its unique recognition effect for NH3, the probe DEMCA-PA could also be applied in food spoilage detection field.

Development of multiple analytical labels for volatile organic compounds based on the results of sorption on CdS quantum dots in chitosan without and with modification with Rhodamine 6G

Analytical solutions using the luminescent labels for the analysis of gaseous media and the detection of volatile organic compounds are discussed. Such solutions can potentially be applied for the development of optical, sorption gas sensors, smart label fillers, test systems with various carriers for the detection of chemical biomarkers in living systems. To solve the problem it is proposed to develop and study the properties of modifiers based on cadmium sulfide quantum dots. The aim of the work is studying the sorption properties of CdS quantum dots prepared using a method improved in the direction of "green chemistry", with stabilizing chitosan shells (pure and modified with Rhodamine 6G). Sorption properties of various phases based on quantum dots were studied at a temperature of 22±1 °C by a highly sensitive direct piezo-quartz microweighting method with a resolution of up to 10–9 g by the mass of the sorbent in vapors of volatile compounds. The selectivity of phases based on cadmium sulfide quantum dots in low-mass chitosan (5–10 micrograms) with respect to volatile organic compounds of different classes was evaluated. The relative selectivity and sensitivity of vapor weighing on different phases were evaluated using the parameters A(i/j), showing how many times the sorption properties of CdS phases in chitosan differ without and with the addition of Rhodamine 6G. The method of direct weighing allows to estimate the rate of sorption and desorption, and the capacity of the sorbent phases. It was established that substances belonging to the same selectivity group in terms of A(i/j) values, for example, water and ethanol, have different sorption rates. This feature can be applied for solving the problems of separate detection of vapors, they can be identified at different moments of exposure of piezo balances with phases based on CdS quantum dots in chitosan without and with the addition of Rhodamine 6G. The use of cadmium sulfide quantum dots in chitosan as a sorbent of organic compound vapors significantly affects the kinetics and sorption efficiency. Modification of chitosan with Rhodamine 6G changes the sorption properties of quantum dots in chitosan, which can be used for engineering new sorbents for sensor systems. Simple algorithms are proposed for solving problems of vapor recognition of volatile compounds according to calculated parameters even for non-selective sorption systems. Programming the approach can significantly increase the expressiveness of decision-making in integrated analytical systems, for example, "electronic noses" based on sensors, including those with studied phases. It was found that the mass of the phase based on cadmium sulfide quantum dots in chitosan does not affect the sorption properties in the micromass range, which is traditional for nanostructures. Changes in the luminescent properties of phases based on cadmium sulfide, as a possible visually detectable analytical response, will be discussed in the next paper.

Molecularly imprinted sol-gel/Au@Ag core-shell nano-urchin localized surface plasmon resonance sensor designed in reflection mode for detection of organic acid vapors

A molecularly imprinted sol-gel (MISG)/Au@Ag core-shell NU sensor is proposed for organic vapor detection in an optical fiber-based reflection mode. The compact structure design of the system in the reflection model is promising for practical use as a portable and rapid responsivity sensing probe. Volatile organic acids (OAs) are analogs to biogenetic volatile organic vapors related to specific human diseases. Here, Au@Ag core-shell nano-urchins exhibiting branched tips were synthesized and deposited on indium tin oxide (ITO) glass in small dimer and trimmer clusters to generate an enhanced electric field. A MISG solution was then spin-coated on the substrate to fabricate MISG-LSPR sensors, and three types of MISGs were developed for the detection of hexanoic acid, heptanoic acid and octanoic acid. The normalized spectral response indicated selectivity of the MISG-LSPR sensors for the corresponding template OAs. With Native Bayes and linear discriminant analysis of the sensor responses, where the latter were detected by the proposed system, single- and mixed-OA vapors could be classified into separate clusters. This signified that the proposed MISG-LSPR sensor can be applied toward pattern recognition of single vapors or multiple vapor mixtures.

Polyvinyl Alcohol/Polypyrrole/Molecularly Imprinted Polymer Nanocomposite as Highly Selective Chemiresistor Sensor for 2,4‐DNT Vapor Recognition

AbstractIn this research, a chemiresistor sensor coated with the polyvinyl alcohol/polypyrrole/molecularly imprinted polymer (PVA/PPy/MIP) nanocomposite was designed and fabricated to detect the vapor of 2,4‐DNT as a nitroaromatic explosive material. The molecularly imprinted polymer was composed of molecular nanoparticles containing cavities compatible with DNT; while, the nanoparticles were synthesized using PVA and glutaraldehyde as functionalized polymer and cross‐linking agent, respectively. Composition and chemical properties of the synthesized MIP and PPy nanoparticles were investigated using scanning electron microscopy (SEM), infrared Fourier transform spectroscopy (ATR‐FTIR), and X‐ray diffraction (XRD) analyses. Results indicated that the nanoparticles of polypyrrole and the synthesized MIP have an average particle sizes of 56 nm and 45 nm, respectively. Afterwards, sensor surface was coated by a thin layer of nanocomposite composed of PVA, the PPy and MIP nanoparticles. The prepared sensors were calibrated and performance‐tested in a static setup. The developed sensor was used to measure different concentrations (0.1–150 ppm) of the explosive vapor. The coated sensor presented a linear range of response within the concentration range of 0.1–70 ppm. Also, selectivity tests were carried out in the presence of DNT and vapor of other organic matters and the results indicated that the designed sensor possesses high sensitivity and selectivity toward DNT.

Compact prototype microfabricated gas chromatographic analyzer for autonomous determinations of VOC mixtures at typical workplace concentrations

This report concerns a benchtop prototype instrument containing a gas chromatographic microanalytical system (μGC) designed for the selective determination of multiple airborne volatile organic compounds (VOCs) at concentrations in the vicinity of recommended occupational exposure limits. The core microsystem consists of a set of discrete Si-microfabricated devices: a dual-cavity, adsorbent-packed micro-preconcentrator-focuser (μPCF) chip that quantitatively captures and thermally desorbs/injects VOCs with vapor pressures between ~0.03 and 13 kPa; tandem micro-column (μcolumn) chips with cross-linked PDMS wall-coated stationary phases capable of temperature-programmed separations; and an integrated array of five μchemiresistors (μCR) coated with different thiolate-monolayer protected gold nanoparticle (MPN) interface films that quantifies and further differentiates among the analytes by virtue of the response patterns generated. Other key components include a pre-trap for low-volatility interferences, a split-flow injection valve, and an onboard He carrier–gas canister. The assembled unit measures 19×30×14 cm, weighs ~3.5 kg, operates on AC power, and is laptop/LabVIEW controlled. Component- and system-level tests of performance demonstrated injection bandwidths <1 s, a μcolumn capacity of ≥8 μg injected mass, linear calibration curves, no humidity effects, excellent medium-term (that is, 1 week) reproducibility, autonomous operation for 8 h, detection limits below Threshold Limit Values (TLV) for 10 mL air samples collected in 1 min, and response patterns that enhanced vapor recognition. The determination of a 17-VOC mixture in the presence of seven interferences was performed in 4 min. Results augur well for adapting the microsystem to an all-MEMS wearable μGC currently under parallel development.

Towards the Nanosheet-Based Photonic Nose: Vapor Recognition and Trace Water Sensing with Antimony Phosphate Thin Film Devices.

A 2D nanosheet-based photonic nose for vapor identification is presented. A HSbP2 O8 nanosheet thin-film sensor with resistive readout is developed for the tracking of trace amounts of water, and a photonic HSbP2 O8 /TiO2 multilayer structure is effective at optically distinguishing between chemically similar solvent vapors through analyte-specific host-guest interactions.

A fully electronic microfabricated gas chromatograph with complementary capacitive detectors for indoor pollutants.

This paper reports a complete micro gas chromatography (μGC) system in which all the components are lithographically microfabricated and electronically interfaced. The components include a bi-directional Knudsen pump, a preconcentrator, separation columns and a pair of capacitive gas detectors; together, these form the iGC3.c2 system. All the fluidic components of the system are fabricated by a common three-mask lithographic process. The Knudsen pump is a thermomolecular pump that provides air flow to the μGC without any moving parts. The film heaters embedded in the separation columns permit temperature programming. The capacitive detectors provide complementary response patterns, enhancing vapor recognition and resolving co-eluting peaks. With the components assembled on printed circuit boards, the system has a footprint of 8×10 cm2 . Using room air as the carrier gas, the system is used to experimentally demonstrate the analysis of 19 chemicals with concentration levels on the order of parts per million (p.p.m.) and parts per billion (p.p.b.). The tested chemicals include alkanes, aromatic hydrocarbons, aldehydes, halogenated hydrocarbons and terpenes. This set of chemicals represents a variety of common indoor air pollutants, among which benzene, toluene and xylenes (BTX) are of particular interest.

Graphene/graphite/molecularly imprinted polymer nanocomposite as the highly selective gas sensor for nitrobenzene vapor recognition

A novel graphene-based chemiresistor gas sensor was introduced for nitrobenzene vapor detection. A molecularly imprinted polymer (MIP) containing the cavities compatible with nitrobenzene molecules was synthesized using methacrylic acid and vinyl benzene as the functional monomers. The imprinted polymeric particles were mixed with graphene to produce a nanocomposite chemiresistor gas sensor. The presence of graphite alongside graphene in the nanocomposite was found to be necessary to achieve a proper difference between the MIP and non-imprinted polymer (NIP)-based sensors. It was found that the addition of poly(methyl methacrylate) in the nanocomposite composition led to better physical durability, enhanced selectivity and higher resistance against humidity effect. Central composite experimental design was utilized to optimize the sensor influencing parameters. The response of the prepared sensor was reversible and a relative standard error equal to 3.5% was obtained for 3 separate determinations. The sensor showed linear response in the concentration range of 0.50–60.0ppm. The detection limit was calculated to be 0.2 parts per million (S/N).

Utilizing diversified properties of monolayer protected gold nano-clusters to construct a hybrid sensor array for organic vapor detection

The present study demonstrated improvement in the vapor recognition rate of a sensor array employing monolayer-protected gold nano-clusters (MPCs) by combining two different MPC transduction properties. The number of sensors was increased by using the same set of MPC materials on different platforms and combined them as a hybrid array. Resistive changes in MPC film due to the insufficient swelling of inter-particle distance, which resulted from nature of absorbed vapor and surface thiolates, provided information in addition to the mass increases during vapor sorption. Quartz crystal microbalance (QCM) was used as the mass-change transducer and MEMS-fabricated interdigit electrode was used as the resistive transducer. Four different thiolate ligands were used to cap the gold core for diversification of the chemical selectivity. Fifteen organic vapors with various functional groups were tested for QCM and chemiresistor (CR) presence. Cluster analysis indicated that the arrays of QCMs and CRs show different selectivity for these 15 VOCs. Linear discriminant analyses (LDA) showed that single-compound identification rates within the response data library of 15 VOCs were 87.7% for the 4-QCM array, 82.1% for the 4-CR array, and 96.1% when a hybrid array of 8-sensors was used. This result proves that different properties of the same MPC can be used as different sensors to increase sensor numbers, and, therefore, to improve recognition rates via a hybrid platform.

Chemometric analysis of gas chromatographic peaks measured with a microsensor array: Methodology and performance assessment

A hybrid multivariate curve resolution method that combines evolving factor analysis (EFA) with alternating least squares (ALS) is applied to simulated partially overlapping binary gas chromatographic (GC) peaks from a microsensor array detector. Extended disjoint principal component regression is then used to relate the results of EFA–ALS to vapor recognition probabilities. The application of this methodology to such data is illustrated and the performance is evaluated. Responses to a set of organic vapors obtained from a portable GC with a detector consisting of an array of four nanoparticle-coated chemiresistors (CR) are used to derive the absolute and relative sensitivity values for the modeling and simulations performed. From these, seven vapor pairs spanning a range of pattern similarity are selected and modeled as Gaussian peaks whose magnitudes and degrees of overlap are varied by simulation. Performance is assessed as a function of the response pattern similarity, chromatographic resolution, signal-to-noise ratio, and the relative response ratio of the composite peak constituents. Overall, despite the low dimensionality of the array data, EFA–ALS provides an effective means of extracting information about co-eluting components from the GC-microsensor array system, and the array provides sufficient diversity of responses to identify those components in most cases, provided that the relative response ratio is <20:1.

Polymer-Coated Gold Island Films as Localized Plasmon Transducers for Gas Sensing

Ultrathin (typically < or = 10-nm thick) gold island films evaporated on transparent substrates show a prominent localized surface plasmon (SP) extinction in the visible-to-NIR range. Changes in the dielectric properties of the contacting medium influence the SP absorption band, providing a scheme for optical sensing based on refractive index change. In the present work, the gas sensing capability of gold island based localized surface plasmon resonance (LSPR) transducers was explored using polymeric coatings as the active interface. LSPR transducers were fabricated by spin-coating of polystyrene (PS) or polystyrene sulfonic acid, sodium salt (PSS) onto 5-nm-thick (nominal thickness) gold island films evaporated on silanized glass and annealed. Detailed characterization of the transducers was carried out using high-resolution scanning electron microscopy, cross-sectional transmission electron microscopy, and in situ atomic force microscopy under controlled atmosphere. The hydrophobic PS film exhibits swelling and significant thickness increase upon exposure to chloroform vapor and little or no change in water vapor, whereas the hydrophilic PSS film shows the opposite behavior when exposed to the same vapors. Polymer swelling upon absorption of vapors of good solvents shows a net effect of lowering the effective refractive index in the vicinity of the gold islands, manifested as a characteristic decrease of the SP band intensity and a blue shift of the band maximum. The response, measured for four different vapors, is fast (approximately 15 s) and reversible. It is shown that gold island systems coated with polymeric films can be applied to vapor recognition in an array configuration.

Evaluation of Multitransducer Arrays for the Determination of Organic Vapor Mixtures

A study of vapor recognition and quantification by polymer-coated multitransducer (MT) arrays is described. The primary data set consists of experimentally derived sensitivities for 11 organic vapors obtained from 15 microsensors comprising five cantilever, capacitor, and calorimeter devices coated with five different sorptive-polymer films. These are used in Monte Carlo simulations coupled with principal component regression models to assess expected performance. Recognition rates for individual vapors and for vapor mixtures of up to four components are estimated for single-transducer (ST) arrays of up to five sensors and MT arrays of up to 15 sensors. Recognition rates are not significantly improved by including more than five sensors in an MT array for any specific analysis, regardless of difficulty. Optimal MT arrays consistently outperform optimal ST arrays of similar size, and with judiciously selected 5-sensor MT arrays, one-third of all possible ternary vapor mixtures are reliably discriminated from their individual components and binary component mixtures, whereas none are reliably determined with any of the ST arrays. Quaternary mixtures could not be analyzed effectively with any of the arrays. A "universal" MT array consisting of eight sensors is defined, which provides the best possible performance for all analytical scenarios. Accurate quantification is predicted for correctly identified vapors.

Rapid determination of ETS markers with a prototype field-portable GC employing a microsensor array detector.

The adaptation of a portable gas chromatograph (GC) prototype with several unique design features to the determination of vapor-phase markers of environmental tobacco smoke (ETS) is described. This instrument employs a dual-stage adsorbent preconcentrator, two series-coupled separation columns that can be independently temperature programmed, and a detector consisting of an array of nanoparticle-coated chemiresistors, whose response patterns are used together with retention times for vapor recognition. An adsorbent pre-trap was developed to remove semi-volatile organics from the sample stream. Conditions were established to quantitatively capture two ETS markers, 2,5-dimethylfuran (2,5-DMF) and 4-ethenylpyridine (4-EP, as a surrogate for 3-EP), and to separate them from the 34 most prominent co-contaminants present in ETS using ambient air as the carrier gas. A complete analysis can be performed every 15 min. Projected detection limits are 0.58 and 0.08 ppb for 2,5-DMF and 4-EP, respectively, assuming a 1 L sample volume, which are sufficiently low to determine these markers in typical smoking-permitted environments.

Mats of Functionalized Carbon Nanotubes for Gas/Vapor Sensing

Gas sensing properties of different carbon nanotube (mostly multiwall, MWCNT) mats, based on electrical resistance measurement were investigated in a simple arrangement and found that the sensitivity for different gases or vapors highly depends on the pre-treatment and functionalization of nanotubes. The selectivity of the sensing was demonstrated by building a vapor recognition system based on an array of multitube sensors made of differently functionalized MWCNTs.

개인 휴대 단말기 (PDA)를 기반으로 한 휴대용 E-Nose의 개발

The electronic nose (e-nose) has been used in food industry and quality controls in plastic packaging. Recently it finds its applications in medical diagnosis, specifically on detection of diabetes, pulmonary or gastrointestinal problem, or infections by examining odors in the breath or tissues with its odor characterizing ability. Moreover, the use of portable e-nose enables the on-site measurements and analysis of vapors without extra gas-sampling units. This is expected to widen the application of the e-nose in various fields including point-of-care-test or e-health. In this study, a PDA-based portable e-nose was developed using micro-machined gas sensor array and miniaturized electronic interfaces. The rich capacities of the PDA in its computing power and various interfaces are expected to provide the rapid and application specific development of the diagnostic devices, and easy connection to other facilities through information technology (IT) infra. For performance verification of the developed portable e-nose system, Six different vapors were measured using the system. Seven different carbon-black polymer composites were used for the sensor array. The results showed the reproducibility of the measured data and the distinguishable patterns between the vapor species. Additionally, the application of two typical pattern recognition algorithms verified the possibility of the automatic vapor recognition from the portable measurements. These validated the portable e-nose based on PDA developed in this study.

A matched-profile method for simple and robust vapor recognition in electronic nose (E-nose) system

The vapor recognition performance of electronic nose (E-nose) system can be improved by manipulating the sensor array responses of vapors in profile forms. The sensor array composed of various carbon-black (CB) polymer composites shows featured response profile patterns, varied from vapors to vapors due to different chemical interactions between the arrayed materials and the vapors. These multidimensional sensory data gives more information than collection of the piecemeal signal features, i.e., maximum sensitivity, signal slopes, rising-time. To use them in vapor recognition task, we proposed a novel matched-profile method was proposed, which is based on the typical digital image pattern matching. The degrees of matching between eight different vapors were evaluated by using the proposed method. The vapor responses are measured by the silicon-based gas sensor array with 16 CB polymer composites installed in membrane structure. The results showed higher contrast between matching and non-matching vapors than conventional method. This implies reliable vapor recognition in E-nose system.

Limits of recognition for simple vapor mixtures determined with a microsensor array.

The "limit of recognition" (LOR) has been defined as the minimum concentration at which reliable individual vapor recognition can be achieved with a multisensor array, and methodology for determining the LORs of individual vapors probabilistically on the basis of sensor array response patterns has been reported. This article explores the problems of defining and evaluating LORs for vapor mixtures in terms of the absolute and relative component vapor concentrations, where the mixture must be discriminated from those component vapors and from the subset of possible lower-order component mixtures. Monte Carlo simulations and principal components regression analyses of an extant database of calibrated responses to a set of 16 vapors from an array of 6 diverse polymer-coated surface acoustic wave sensors are used to illustrate the approach and to examine trends in LOR values among the 120 possible binary mixtures and 560 possible ternary mixtures in the data set. At concentrations exceeding the LOD, 89% of the binary mixtures could be reliably recognized (<5% error) over some composite concentration range, while only 3% of the ternary mixtures could be recognized. Most binary mixtures could be recognized only if the constituent vapor relative concentration ratio, defined in terms of multiples of the LOD for each vapor, was < or =20. Correlations with the Euclidean distance(s) separating the normalized constituent vapor response vectors allow reasonably accurate predictions of the limiting recognizable mixture composition ranges for binary and ternary cases. Results are considered in the context of using microsensor arrays for vapor detection and recognition in microanalytical systems.

Portable gas chromatograph with tunable retention and sensor array detection for determination of complex vapor mixtures.

A prototype portable gas chromatograph that combines a multiadsorbent preconcentrator/focuser, a tandem-column separation stage with individual column temperature control and junction point pressure modulation, and a detector consisting of an integrated array of polymer-coated surface acoustic wave microsensors is described. Using scheduled first-column stop-flow intervals and independent temperature programming of the two columns, it is possible to adjust the retention of eluting analyte vapors to maximize vapor recognition with the microsensor array and minimize the time of analysis. A retention window approach is combined with Monte Carlo simulations to guide retention tuning requirements and facilitate pattern recognition analyses. The determination of a 30-vapor mixture of common indoor air contaminants in < 10 min is demonstrated using ambient air as the carrier gas. Detection limits of < 10 ppb are achieved for the majority of compounds from a 1-L air sample on the basis of the most sensitive sensor in the array. Performance is assessed in the context of near-real-time indoor air quality monitoring applications.

Dual-Chemiresistor GC Detector Employing Monolayer-Protected Metal Nanocluster Interfaces

The synthesis and testing of two gold-thiolate monolayer-protected (nano)clusters as interfacial layers on a dual-chemiresistor vapor sensor array are described. Responses (changes in dc resistance) to each of 11 organic solvent vapors are rapid, reversible, and linear with concentration at low vapor concentrations, becoming sublinear at higher concentrations. Limits of detection (LODs) range from 0.1 to 24 parts per million and vary inversely with solvent vapor pressure. When configured as a GC detector and used to analyze 0.5-L preconcentrated samples of the 11-vapor mixture, the array provides LODs of < or = 700 parts per trillion for most vapors, comparing favorably with those from an integrated array of polymer-coated surface acoustic wave sensors configured and tested similarly. This first report on the use of such an array as a GC detector shows that the combination of response patterns and GC retention times improves capabilities for vapor recognition compared to the sensor array alone or to single-detector GC systems. Spray-coated nanocluster thin films can be deposited reproducibly and exhibit response stability in air that ranges from fair to excellent for up to several months. Scaling the active device area down by a factor of 16 has no significant effect on sensitivity. Implications of these results for portable vapor sensing systems are discussed.

Vapor recognition with an integrated array of polymer-coated flexural plate wave sensors

Preliminary testing of a prototype instrument employing an integrated array of six polymer-coated flexural plate wave (FPW) sensors and an adsorbent preconcentrator is described. Responses to thermally desorbed samples of individual organic solvent vapors and binary and ternary vapor mixtures are linear with concentration, and mixture responses are equivalent to the sums of the responses of the component vapors, which co-elute from the preconcentrator in most cases. Limits of detection as low as 0.3 ppm are achieved from a 60-s (34 cm 3) air sample and peak widths at half-maximum range from 1 to 4 s. Tests at different flow rates suggest that the kinetics of vapor sorption in the sensor coating films may limit responses at higher flow rates, however, low data acquisition rates may also be contributory. Assessments of array performance using independent test data and Monte Carlo simulations with pattern recognition indicate that individual vapors and certain binary and ternary mixtures can be recognized/discriminated with very low error. More complex mixtures, and those containing homologous vapors, are problematic. This is the first report demonstrating multi-vapor analysis with an integrated FPW sensor array.