[Object] To provide a compact and reusable alkene-detection gas sensor that detects an alkene and a system using the same.

[Solving Means] An alkene-detection gas sensor that detects an alkene in a sample gas according to the present invention includes: a first reaction unit that contains a palladium catalyst and oxidizes an alkene in a sample gas to convert the alkene into an aldehyde and/or a ketone; a second reaction unit that contains hydroxylamine salts and reacts with the aldehyde and/or ketone converted in the first reaction unit to generate an acid; and a response unit that includes an electrode supporting a semiconductor material of which an electrical resistance value changes by the generated acid, in which the palladium catalyst, the hydroxylamine salts, and the semiconductor material are separated from each other.

The present invention relates to a system for analysing volatile organic compounds (VOCs) in soil comprising an apparatus and a soil VOC sensor strip, wherein the apparatus comprises a sampling chamber for receiving soil, a sensor strip aperture in the sampling chamber for positioning the sensor strip in fluid communication with the sampling chamber, a power source and an electrical resistance detector, wherein the sensor strip comprises a flexible substrate with a first surface and an array of semiconductor polymer sensors arranged on the first surface, wherein each of the semiconductor polymer sensors comprises a pair of electrodes, wherein the pair of electrodes comprises a first electrode and a second electrode, wherein a semiconductor polymer is disposed between the first electrode and the second electrode, and wherein the sensor strip is electrically connectable to the power source and the electrical resistance detector.

According to one embodiment, a sensor includes a base, first and second detection element portions, first to third resistor terminals, and first and second conductive terminals. The base includes first and second base regions. The first detection element portion is provided at the first base region. The first detection element portion includes a first detection dement. The first detection dement includes a first resistance member and a first conductive member. The first resistance member includes a first resistance portion and other portion. The first conductive member includes a first conductive portion and other portion. The second detection element portion is provided at the second base region. The second detection dement portion includes a second detection element. The second detection element includes a second resistance member and a second conductive member. The second resistance member includes a second resistance portion and other portion. The second conductive member includes a second conductive portion and other portion.

In some embodiments, data from multiple vehicle-based natural gas leak detection survey runs are used by computer-implemented machine learning systems to generate a list of natural gas leaks ranked by hazard level. A risk model embodies training data having known hazard levels, and is used to classify newly-discovered leaks. Hazard levels may be expressed by continuous variables, and/or probabilities that a given leak fits within a predefined category of hazard (e.g. Grades 1-3). Each leak is represented by a cluster of leak indications (peaks) originating from a common leak sources. Hazard-predictive features may include maximum, minimum, mean, and/or median CH4/amplitude of aggregated leak indications; estimated leak flow rate, determined from an average of leak indications in a cluster; likelihood of leak being natural gas based on other indicator data (e.g. ethane concentration); probability the leak was detected on a given pass; and estimated distance to leak source.

A method of preparing electronically conductive polyaniline that forms a self-supporting dispersion in water is described. The binder-free dispersion was coated on a pair of interdigitated metal electrodes to form a gas sensing layer of a chemical sensor. The chemical sensor utilizes electrochemical impedance spectroscopy (EIS) to detect and characterize a chemical compound in a gaseous state in contact with the sensing layer. Impedance of the sensing layer is measured over a range of alternating current frequencies. The impedance data allows identification and concentration of the chemical compound to be determined when compared to reference impedance data. The analysis of the impedance measurements is adaptable to machine learning.

A method for monitoring air quality is described. The method includes measuring ethane and methane using a mobile sensor platform to provide sensor data. The sensor data includes methane data and ethane data captured at a nonzero mobile sensor platform speed. Methane and ethane peak(s) are identified in the sensor data. Correlation(s) between the methane and ethane peak(s) and/or between the methane peak(s) and at least one amount of .sup.13C are determined. A source for the methane is determined based on the correlation.

A method for analyzing a gaseous pollutant by means of a microfluid circuit includes a means for pumping a liquid and a means for trapping a gas, comprising the following steps: a) generating a flow of a liquid, the liquid comprising a selective derivative agent; b) trapping and dissolving gaseous pollutant in the flow; c) reaction of the pollutant with the selective derivative agent so as to form a liquid derivative compound; d) measuring the concentration of liquid derivative compound and determining the concentration of gaseous pollutant.

A hybrid gas sampling device can combine the functionality of both whole air and sorbent based samplers. The sampling device can be used for collecting light to very heavy organic compounds, for subsequent thermal desorption into a GC or GCMS for quantitative measurement. The sampling device isolates collected samples of gas phase matrices in a sample vessel, provided with sorbent elements from a removable sample extraction device. The sampling device is operated by drawing a vacuum on the chamber through the sample extraction device after sampling, and then completing the extraction of the heavier organic compounds using a static, diffusive extraction under vacuum to allow optimal deposition of the heavier compounds on the sorbent. The vacuum container is cooled to draw any excess water back into the container, thereby dehydrating attached sorbent element(s) in preparation for thermal desorption into a GC or GCMS, eliminating interferences in the MS analyzer.

Micro gas chromatographic devices are provided having a microfluidic separation column and a plurality of capillaries where the capillaries have been independently configured in terms of the capillary length, capillary width, the packing density and packing geometry of the capillary using one or more micro pillars, the tortuosity of the capillary path, and the presence and identity of the stationary phase for use in micro gas chromatographic separation of complex mixtures of compounds. Through the plurality of capillaries, the devices are capable of discriminating between complex samples even in instances where complete separation of the components is not possible. Methods of fabrication and methods of use of the devices are also provided. The devices can be readily fabricated using known techniques. The devices can be used for the analysis of complex mixtures of compounds containing tens or hundreds of compounds in which just a few differ in presence or concentration.

The present invention describes methods of using Olfr90 demonstrated to bind to fungal metabolites, including a metabolite known to be detected in patients with mold (e.g. Aspergillus) infections.