Sensing characteristics of the organic vapors according to the reflectance spectrum in the porous silicon multilayer structure

We fabricated a porous silicon multilayer and investigated its reflectance spectra before, during, and after exposure to various organic vapors. During exposure of the porous silicon multilayer to isopropanol, ethanol, methanol, and acetone vapors, the reflectance peak shifted toward longer wavelengths by about 5, 12, 26, and 39 nm, respectively. The shift of the reflectance peak arises from refractive index changes induced by capillary condensation of the organic vapor in the pores of the porous silicon multilayer. In addition, we observed that the shift value of the reflectance peak increased with increasing organic solvent concentration in the organic solvent-water mixture. After removing the organic vapor, the reflectance spectrum returned completely to its original state.     

Mimicking the sense of olfaction: A conducting-polymer-based electronic nose

Abstract— We describe herein the construction of a simple, low-power, broadly responsive vapor sensor. Carbon-black-organic-polymer composites have been shown to swell reversibly upon exposure to vapors. Thin films of carbon-black-organic-polymer composites have been deposited across two metallic leads, with swelling-induced resistance changes of the films signaling the presence of vapors. To identify and classify vapors, arrays of such vapor-sensing elements have been constructed, with each element containing a different organic polymer as the insulating phase. The differing gas-solid partition coefficients for the various polymers of the sensor array produce a pattern of resistance changes that can be used to classify vapors and vapor mixtures. This type of sensor array has been shown to resolve all organic vapors that have been analyzed, and can even resolve H²O from D²O.     

Optical parameters of calix[4]arene films and their response to volatile organic vapors

The Langmuir-Blodgett (LB) technique was employed to produce thin LB films using an amphiphilic calix-4-resorcinarene onto different substrates such as quartz, gold coated glass and quartz crystals. The characteristics of the calix LB films are assessed by UV-visible, quartz crystal microbalance (QCM) and surface plasmon resonance (SPR) measurements. UV-vis and QCM measurements indicated that this material deposited very well onto the solid substrates with a transfer ratio of >0.95. Using SPR data, the thickness and refractive index of this LB film are determined to be 1.14 nm/deposited layer and 1.6 respectively. The sensing application of calixarene LB films towards volatile organic vapors such as chloroform, benzene, toluene and ethanol vapors is studied by the SPR technique. The response of this LB film to saturated chloroform vapor is much larger than for the other vapors. The response is fast and fully recoverable. It can be proposed that this sensing material deposited onto gold coated glass substrates has a good sensitivity and selectivity for chloroform vapor. This material may also find potential applications in the development of room temperature organic vapor sensing devices.     

Vapor sensing properties of thermoplastic polyurethane multifilament covered with carbon nanotube networks

The volatile organic compound (VOC) vapor sensing properties of a novel kind of thermoplastic polyurethane multifilament - carbon nanotubes (TPU-CNTs) composites is studied. And the sensing is based on changes in the electrical resistance of the composites due to vapor contact. The composites were readily obtained by adhering CNTs on the surface layer of TPU by means of simply immersing pure TPU multifilament into CNT dispersion. The uniformly formed nanotube networks on the outer layer of composite multifilament are favorable for providing efficient conductive pathways. The resulting TPU-CNTs composites show good reproducibility and fast response (within seconds) of electrical resistance change in cyclic exposure to diluted VOC and pure dry air. The vapor sensing behaviors of the composites are related to CNT content, vapor concentration, and polar solubility parameters of the target vapors. A relatively low vapor concentration of 0.5% is detectable, and a maximum relative resistance change of 900% is obtained for the composite with 0.8 wt.% CNT loading when sensing 7.0% chloroform. It is proposed that both the disconnection of CNT networks caused by swelling effects of the TPU matrix and the adsorption of VOC molecules on the CNTs are responsible for the vapor sensing behavior of TPU-CNTs composite, while the former effect plays the major role.     

Chemo-sensitivity of latex-based films containing segregated networks of carbon nanotubes

In contrast to conventional hydrophobic Conductive Polymer nanoComposites (CPCs) used to design vapor sensors, which are mostly soluble in organic solvents, monodispersed acrylate copolymer latexes present the double advantage of being more sensitive and selective towards polar vapors such as water. A hierarchically structured latex based CPC film was obtained by co-dispersion of an aqueous acrylic emulsion with multiwalled carbon nanotubes (CNTs), followed by spray layer by layer (sLbL) assembly. The analysis of CPC films morphology by AFM and TEM show that a segregated network of CNT as been achieved by partial coalescence of latex nanoparticles and homogeneously assembled in 3D. Transducer sensitivity was investigated as a function of CNT content, latex glass transition temperature (T_g), organic vapor nature and vapor concentration. The source of the high sensitivity and selectivity observed for these latex-based composites towards water vapor is assumed to mainly result from ionic interaction of SDS with water molecules offering interesting perspectives of development. The different diffusion regimes through the CPC transducer are visualized, modeled and interpreted with the Langmuir-Henry-Clustering (LHC) model, showing that only water is reaching a clustering mode at high vapor concentration. Finally it is believed that the unique hierarchical architecture of BA latex-CNT sensors is responsible for their quick, stable and reproducible responses to vapors.     

Composites of carboxylate-capped TiO2 nanoparticles and carbon black as chemiresistive vapor sensors

Titanium (IV) dioxide (TiO₂) nanoparticles (NPs) with a 1-5 nm diameter were synthesized by a sol-gel method, functionalized with carboxylate ligands, and combined with carbon black (CB) to produce chemiresistive chemical vapor sensor films. The TiO₂ acted as an inorganic support phase for the swellable, organic capping groups of the NPs, and the CB imparted electrical conductivity to the film. Such sensor composite films exhibited a reproducible, reversible change in relative differential resistance upon exposure to a series of organic test vapors. The response of such chemiresistive composites was comparable to, but generally somewhat smaller than, that of thiol-capped Au NPs. For a given analyte, the resistance response and signal-to-noise ratio of the capped TiO₂-NP/CB composites varied with the identity of the capping ligand. Hence, an array of TiO₂-NP/CB composites, with each film having a compositionally different carboxylate capping ligand, provided good vapor discrimination and quantification when exposed to a series of organic vapors. Principal components analysis of the relative differential resistance response of the sensor array revealed a clear clustering of the response for each analyte tested. This approach expands the options for composite-based chemiresistive vapor sensing, from use of organic monomeric or polymeric sorbent phases, to use of electrically insulating capped inorganic NPs as the nonconductive phase of chemiresistive composite vapor sensors.     

可视嗅觉传感器阵列研究及图像分析

针对目前电子鼻系统普遍存在的检测范围窄、受环境湿度影响较大等缺点,本文依据金属卟啉配合物与有机气体反应会产生颜色变化的原理,研制了一种新型的气体敏感膜,设计了可视嗅觉传感器阵列的实验系统.系统通过分析敏感膜与不同的气体反应所呈现的颜色变化识别气体,具有完全不受外界水蒸气影响和检测精度高等特点.用该传感器敏感膜分别对环己胺、乙腈和四氢呋喃进行了试验,试验结果表明该传感器阵列能够正确地识别这三种有机物.     

一种基于多孔硅微腔光学特性的气体传感器的研究

当有机物分子吸附到多孔硅表面时,由于有机物分子在多孔硅的孔内的毛细冷凝作用,将引起多孔硅层有效折射率的变化,从而导致多孔硅微腔反射谱吸收峰峰位的变化.本文主要利用Bruggeman介电常数近似理论与传输矩阵的方法,建立了多孔硅微腔的传感模型.使用多孔硅微腔的反射谱实验装置对多孔硅微腔进行了传感实验,结果证明多孔硅微腔传感元件可以实现对有机物蒸汽的检测,且分辨率较高,响应时间和恢复时间短,可重复性好.     

Thin film characterization and vapor sensing properties of a novel perylenediimide material

A novel N,N′-(glycine tert-butylester)-3,4,9,10-perylenediimide was chosen for the study of Langmuir–Blodgett (LB) thin film characterization and the sensing properties against selected volatile organic vapors. Different number of LB film layer was deposited onto a glass and quartz crystal substrate. The thin film fabrication process was monitored with UV–vis and quartz crystal microbalance (QCM) measurement techniques. The results indicated that absorbance increased linearly with the number of the layers on film. A similar linear relationship between frequency shift and number of the layers was observed by the QCM measurement. It can be concluded that high quality and uniform LB films were produced by using this novel perylenediimide material. Chloroform, toluene, benzene, ethyl alcohol and isopropyl alcohol vapors were selected to test this material's applicability in room temperature as a vapor sensor. This novel material showed a fast, large and reproducible response to chloroform and isopropyl alcohol vapor.     

Effect of soft-hard segment structure on vapor responsiveness of polyurethane conducting composite thin films loaded with multi-walled carbon nanotubes

A series of multi-walled carbon nanotubes/polyurethane (MWNTs/PU) composite conducting dispersoids were prepared via an in situ coupling reaction among linear hydroxyl-terminated polymer diols, 1,6-hexamethylene diisocyanate (HDI) and various chain extenders. The composite conducting thin films were formed by spin-coating and depositing the dispersoids onto comb-like electrode substrates. The resulting structure and the dispersion quality of MWNTs in the dispersoids were examined by means of FTIR, XRD, TEM, SEM and UV-vis analyses. The response of the as-prepared films toward some volatile organic solvent vapors such as benzene, anhydrous ether, acetone and chloroform was evaluated. The experimental results indicated that the composite conducting films constructed by hydroxyl-terminated poly(butadiene-co-acrylonitrile), trimethylolpropane, and MWNTs-OH bear better vapor responsiveness. The dispersion behavior of MWNTs in the dispersoids, types of MWNTs and soft-hard segmental compositions are believed to be closely related with the sensing properties of the films. In particular, the chemical linkage of MWNT-OH with HDI in the PU matrix is expected to improve the dispersivity and further to enhance the sensing properties of the composite sensors. The vapor sensing properties well reveal that these materials have a possibility as a candidate of volatile organic solvent vapor sensors.     

On-chip Fabry-Pérot interferometric sensors for micro-gas chromatography detection

We fabricated and characterized on-chip Fabry-Pérot (FP) vapor sensors for the development of on-column micro-gas chromatography (μGC) detectors. The FP sensors were made by coating a thin layer of polymer on a silicon wafer. The air-polymer and polymer-silicon interfaces form an FP cavity, whose resonance wavelengths change in response to the vapor absorption/desorption, thus allowing for rapid detection and quantification of vapors. For proof-of-concept, two polymers (PDMS and SU-8) were used independently and placed in an array in a microfluidic channel, and showed different sensitivities for different vapors. A sub-nano-gram detection limit and sub-second response time were achieved, representing orders of magnitude improvement over those previously reported. This on-chip design will enable the unprecedented integration of optical vapor sensors with μGC systems.     

Assessment of water quality in Lake Garda (Italy) using Hyperion

For testing the integration of the remote sensing related technologies into the water quality monitoring programs of Lake Garda (the largest Italian lake), the spatial and spectral resolutions of Hyperion and the capability of physics-based approaches were considered highly suitable. Hyperion data were acquired on 22nd July 2003 and water quality was assessed (i) defining a bio-optical model, (ii) converting the Hyperion at-sensor radiances into subsurface irradiance reflectances, and (iii) adopting a bio-optical model inversion technique. The bio-optical model was parameterised using specific inherent optical properties of the lake and light field variables derived from a radiative transfer numerical model. A MODTRAN-based atmospheric correction code, complemented with an air/water interface correction was used to convert Hyperion at-sensor radiances into subsurface irradiance reflectance values. These reflectance values were comparable to in situ reflectance spectra measured during the Hyperion overpass, except at longer wavelengths (beyond 700 nm), where reflectance values were contaminated by severe atmospheric adjacency effects. Chlorophyll-a and tripton concentrations were retrieved by inverting two Hyperion bands selected using a sensitivity analysis applied to the bio-optical model. The sensitivity analysis indicated that the assessment of coloured dissolved organic matter was not achievable in this study due to the limited coloured dissolved organic matter concentration range of the lake, resulting in reflectance differences below the environmental measurement noise of Hyperion. The chlorophyll-a and tripton image-products were compared to in situ data collected during the Hyperion overpass, both by traditional sampling techniques (8 points) and by continuous flow-through systems (32 km). For chlorophyll-a the correlation coefficient between in situ point stations and Hyperion-inferred concentrations was 0.77 (data range from 1.30 to 2.16 mg m^− 3). The Hyperion-derived chlorophyll-a concentrations also match most of the flow-through transect data. For tripton, the validation was constrained by variable re-suspension phenomena. The correlation coefficient between in situ point stations and Hyperion-derived concentrations increased from 0.48 to 0.75 (data range from 0.95 to 2.13 g m^− 3) if the sampling data from the re-suspension zone was avoided. The comparison of Hyperion-derived tripton concentrations and flow-through transect data exhibited a similar mismatch. The results of this research suggest further studies to address compatibilities of validation methods for water body features with a high rate of change, and to reduce the contamination by atmospheric adjacency effects on Hyperion data at longer wavelengths in Alpine environment. The transferability of the presented method to other sensors and the ability to assess water quality independent from in situ water quality data, suggest that management relevant applications for Lake Garda (and other subalpine lakes) could be supported by remote sensing.     

Non-solvent induced phase separation as a method for making high-performance chemiresistors based on conductive polymer nanocomposites

The fabrication of novel porous conductive composite vapor sensors characterized by different porosities and specific surface areas is described in this study. These samples were obtained by the dry-cast non-solvent induced phase separation (NIPS) method. Porous composite structures have been studied by the SEM, BET and water evaporation methods. Testing different concentrations of several organic vapors, the porous sensors showed improved sensitivities and response times as compared to their dense counterpart. Improved characteristics of the sensor response were correlated to better sorption and diffusion properties of sensing film due to increased porosity and specific surface area obtained by this method of film fabrication. A competition theory was proposed that describes the optimum porosity and thickness of sensing films in which the highest sensitivities were observed.     

Improved reversibility in aged porous silicon NO2 sensors

Porous silicon (PS) conductometric gas sensors can exhibit large sensitivity to gases, due to the large surface versus volume ratio of porous silicon. A possible application is the detection of traces of nitrogen dioxide (NO₂), an air pollutant. ΔG/G signals in excess of 10 in the presence of concentrations as low as 50 ppb in dry air can be demonstrated. Unfortunately, such high sensitivity to NO₂ is achieved, in fresh samples, with poor reversibility. Another problem is the interference of water vapor, which also affects the porous silicon conductivity. However, we show that reversibility is complete in aged samples, and sensitivity to water vapor is lowered. Although in aged samples large ΔG/G signals are harder to achieve, we show that concentration levels of NO₂ at few tens of ppb are still detectable.     

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 cm³) 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.     

Modeling Carbon-Black/Polymer Composite Sensors

Conductive polymer composite sensors have shown great potential in identifying gaseous analytes. To more thoroughly understand the physical and chemical mechanisms of this type of sensor, a mathematical model was developed by combining two sub-models: a conductivity model and a thermodynamic model, which gives a relationship between the vapor concentration of analyte(s) and the change of the sensor signals. In this work, 64 chemiresistors representing eight different carbon concentrations (8-60 vol% carbon) were constructed by depositing thin films of a carbon-black/polyisobutylene composite onto concentric spiral platinum electrodes on a silicon chip. The responses of the sensors were measured in dry air and at various vapor pressures of toluene and trichloroethylene. Three parameters in the conductivity model were determined by fitting the experimental data. It was shown that by applying this model, the sensor responses can be adequately predicted for given vapor pressures; furthermore the analyte vapor concentrations can be estimated based on the sensor responses. This model will guide the improvement of the design and fabrication of conductive polymer composite sensors for detecting and identifying mixtures of organic vapors.     

微结构参数对多孔硅层热绝缘性能的影响

研究了多孔硅层厚度,孔隙率以及多孔硅中微晶粒尺寸三个微结构参数对其热绝缘性的影响机制.实验选用p ,p-两种掺杂浓度的硅片基底,采用电化学腐蚀法,通过改变腐蚀时间和腐蚀电流密度获得不同微结构参数的多孔硅层.分别采用显微拉曼光谱法及测量显微镜聚焦法测量了样品的热导率和厚度.研究发现,多孔硅层厚度影响热量传输路径,而孔隙率和微晶粒尺寸通过降低热导率从而使多孔硅的绝热性增强.     

Ionic liquids used as QCM coating materials for the detection of alcohols

Six imidazolium-based ionic liquids (ILs) were synthesized and employed as sensing materials coated on quartz crystal microbalance for the detection of organic vapors. Acetone, ethanol, dichloromethane, benzene, toluene and hexane were selected as representatives for common environmental pollutants, and good linear responses from 0 to 100% of concentrations were observed. The halogen-anion-containing imidazolium ILs-coated sensors showed fast response, excellent reversibility, and considerable sensitivity and selectivity towards alcohols, and the selective factors were up to 30 times for ethanol versus other VOCs. The existence of water vapor reduced the frequency response of the sensor, but a good linear relationship remained.     

Modeling fire severity in black spruce stands in the Alaskan boreal forest using spectral and non-spectral geospatial data

Biomass burning in the Alaskan interior is already a major disturbance and source of carbon emissions, and is likely to increase in response to the warming and drying predicted for the future climate. In addition to quantifying changes to the spatial and temporal patterns of burned areas, observing variations in severity is the key to studying the impact of changes to the fire regime on carbon cycling, energy budgets, and post-fire succession. Remote sensing indices of fire severity have not consistently been well-correlated with in situ observations of important severity characteristics in Alaskan black spruce stands, including depth of burning of the surface organic layer. The incorporation of ancillary data such as in situ observations and GIS layers with spectral data from Landsat TM/ETM+ greatly improved efforts to map the reduction of the organic layer in burned black spruce stands. Using a regression tree approach, the R² of the organic layer depth reduction models was 0.60 and 0.55 (p < 0.01) for relative and absolute depth reduction, respectively. All of the independent variables used by the regression tree to estimate burn depth can be obtained independently of field observations. Implementation of a gradient boosting algorithm improved the R² to 0.80 and 0.79 (p < 0.01) for absolute and relative organic layer depth reduction, respectively. Independent variables used in the regression tree model of burn depth included topographic position, remote sensing indices related to soil and vegetation characteristics, timing of the fire event, and meteorological data. Post-fire organic layer depth characteristics are determined for a large (> 200,000 ha) fire to identify areas that are potentially vulnerable to a shift in post-fire succession. This application showed that 12% of this fire event experienced fire severe enough to support a change in post-fire succession. We conclude that non-parametric models and ancillary data are useful in the modeling of the surface organic layer fire depth. Because quantitative differences in post-fire surface characteristics do not directly influence spectral properties, these modeling techniques provide better information than the use of remote sensing data alone.     

炭黑填充聚乙烯导电复合材料气敏性能研究

采用溶液共混法成功制备出炭黑/聚乙烯导电气敏复合材料,研究了在苯、甲苯、二甲苯三种有机溶剂蒸汽中的电阻变化.实验结果表明,该复合材料在二甲苯蒸汽中电阻变化最大,在苯蒸汽中电阻变化最小.进一步研究了其在100 ppm至800 ppm(ppm=10-6)二甲苯蒸汽中的气敏响应性,实验结果表明:复合材料的灵敏度从0.04增大至0.11.