Odor sensor element for water quality evaluation, odor sensor for water quality evaluation, and water quality evaluation device

Abstract

To provide a water quality evaluation odor sensor element which offers more appropriate sensitivity and stability to target gases generated by waste water and the like.SOLUTION: An odor sensor element (31) for food condition evaluation is provided, comprising a first metal wiring line (313A), a second metal wiring line (313B) spaced apart from the first metal wiring line (313A), and an odor substance receptor layer (315) in contact with at least a portion of the first metal wiring line (313A) and at least a portion of the second metal wiring lie (313B), where the odor substance receptor layer (315) contains a resin composition containing a polyurethane resin, a surfactant, and a conductive carbon material.SELECTED DRAWING: Figure 2

Description

[[Technical Field]]

[0001] The present invention relates to an odor sensor element for water quality evaluation, an odor sensor for water quality evaluation, and a water quality evaluation apparatus for evaluating the water quality of wastewater, raw water for purification, and the like. [[Background Art]]

[0002] With the development of information processing technology in recent years, if olfactory sensation, for which mechanical measurement among human five senses has not been sufficiently achieved, can be quantified by some method, it is expected that the technology can be used in a wide range of industrial fields. For example, the technology can be applied to nursing and care in the medical field, pre-disease prevention diagnosis and disease testing, odor management in factories in the environmental field, fermentation process management and wastewater treatment management in the biogas utilization field, precursor detection of landslides and flood disasters in the safety field, and deterioration detection of engine oil and mechanical operating oil. In addition, in the food field, it can be used for detecting the ripening state of food materials such as plants and meat, process management of fermented foods such as alcoholic beverages, cultivation management of plants, and quality control in the production, storage and distribution processes of foods, and in the marketing field, it can be used for production of cosmetics, body odor, scent environments, and scents of commercial products. To date, methods for detecting specific gaseous substances (gases) have achieved high-accuracy and high-sensitivity measurement using semiconductor gas sensors and the like. Sensors having different response characteristics to various odors have been reported, and studies have also been conducted on the composition of receptors included in the sensors.

[0003] The invention described in Patent Document 1 proposes a mechanism in which the semiconductor of a semiconductor gas sensor is replaced with a conductive polymer to detect the adsorption of odor components on the surface of the conductive polymer. Patent Document 1 reports that this enables detection of odor components that are easily thermally decomposed and substances that do not cause an oxidation-reduction reaction on the surface of the detection portion of a sensor.

[0004] Furthermore, Patent Document 2 focuses on the property that the electrical resistance of a mixture of organic polymers and conductive materials changes when exposed to organic gases. Patent Document 2 describes that when multiple combinations of organic polymers / conductive materials with different organic polymer compositions are prepared and used as an electrical resistance array in a sensor, the change in electrical resistance when exposed to the same organic gas is different for each. Patent Document 2 reports that by utilizing this, odors can be identified by assigning the pattern of change in electrical resistance to the type of odor (i.e., the mixture of organic gases).

[0005] Furthermore, Patent Document 3 reports that adding a plasticizer to the above-mentioned organic polymer improves the response speed of the sensor.

[0006] On the other hand, there are known technologies that attempt to measure odors (smells) emitted from wastewater and raw water for water purification.

[0007] Patent documents 4 and 5 disclose a technology for measuring the odor intensity of wastewater and performing feedback control on wastewater treatment based on the measurement results. Patent document 6 also discloses a technology that uses an odor sensor to measure the concentration of odor substances by changing the resonant frequency or electrical resistance due to the adsorption of odor substances, and stops the intake of raw water for water purification when the odor substance concentration exceeds a standard value. [Prior art documents] [Patent Documents]

[0008] [Patent Document 1] Japanese Patent Application Publication No. 11-23508 [Patent Document 2] Special Publication No. 11-503231 [Patent Document 3] Special Publication No. 2002-519633 [Patent Document 4] Japanese Patent Publication No. 2010-155189 [Patent Document 5] Patent No. 4922214 [Patent Document 6] Japanese Patent Application Publication No. 10-296235 [Overview of the project] [Problems that the invention aims to solve]

[0009] Sensors that measure odors emitted from wastewater and raw water for water purification are inevitably exposed to environments containing moisture. In such environments, sensor degradation progresses, making it difficult to maintain the reliability of measurement results.

[0010] One aspect of the present invention aims to provide a water quality evaluation odor sensor element, a water quality evaluation odor sensor, and a water quality evaluation device that exhibit more appropriate sensitivity and stability to odors. [Means for solving the problem]

[0011] The inventors of this invention arrived at this present invention as a result of their research in order to achieve the above objectives.

[0012] In other words, a water quality evaluation odor sensor element, a water quality evaluation odor sensor, and a water quality evaluation device according to one aspect of the present invention comprises a first metal wiring, a second metal wiring spaced apart from the first metal wiring, and an odor substance receiving layer in contact with at least a portion of the first metal wiring and at least a portion of the second metal wiring, and containing a resin composition comprising a polyurethane resin (A), a surfactant (B), and a conductive carbon material (C). The invention relates to a water quality evaluation odor sensor element, a water quality evaluation odor sensor, and a water quality evaluation device using the same. [Effects of the Invention]

[0013] According to one aspect of the present invention, it is possible to provide a water quality evaluation odor sensor element, a water quality evaluation odor sensor, and a water quality evaluation device that exhibit more appropriate sensitivity and stability. [Brief explanation of the drawing]

[0014] [Figure 1] This is a schematic diagram showing an example of the configuration of an odor sensor according to one embodiment of the present invention. [Figure 2] It is a top view showing an example of the configuration of a sensor element. [Figure 3] It is a cross-sectional view showing an example of the configuration of the sensor element shown in FIG. 2. [Figure 4] It is a schematic diagram showing an example of the configuration of an odor measurement device according to an embodiment of the present invention. [Figure 5] It is a functional block diagram showing an example of the configuration of an odor measurement device. [Figure 6] It is a flowchart showing an example of the process flow in which an estimation device generates an estimation model. [Figure 7] It is a functional block diagram showing an example of the configuration of an odor measurement device. [Figure 8] It is a flowchart showing an example of the process flow in which an estimation device estimates an odor substance. DETAILED DESCRIPTION OF THE INVENTION

[0015] An embodiment of the present invention will be described below, but the present invention is not limited thereto. In addition, unless otherwise specified in the present specification, "A to B" representing a numerical range means "from A to B inclusive".

[0016] [1. Resin Composition] A resin composition according to an embodiment of the present invention is a resin composition for forming an odor substance receptive layer, and comprises a polyurethane resin (A), a surfactant (B) and a conductive carbon material (C).

[0017] In the present specification, the term "odor substance" broadly means a substance that can be adsorbed to the odor substance receptive layer. Accordingly, substances that are not generally regarded as odor-causing substances are also included. An "odor" often contains a plurality of causative odor substances, and there also exist substances that are not recognized as odor substances or unknown odor substances. An embodiment of the present invention focuses on the fact that the adsorption amount of an odor substance to the odor substance receptive layer varies depending on the type of the odor substance.

[0018] In this specification, even when the term "odor substance" is used, it may refer not to an individual odor substance, but to a "collection of odor substances" that may contain multiple odor substances.

[0019] While not particularly limited, examples of "odor substances" include hexane, ethyl acetate, methanol, diethyl carbonate, toluene, d-limonene, bornan-2-one, cis-3-hexenol, β-phenylethyl alcohol, citral, L-carbone, γ-undecalactone, eugenol, linalyl acetate, menthol, benzaldehyde, vanillin, hexanal, ethanol, pentyl valerate, linalool, and 2-propanol.

[0020] Furthermore, in this specification, "odor substance receiving layer" means a layer that adsorbs odor substances to be identified. The odor substance receiving layer is formed from the resin composition described above. The odor substance receiving layer may be provided as part of a sensor element described later.

[0021] The sensor described in Reference 1 is thought to be capable of detecting odors consisting of individual compounds. However, many odors are mixtures of multiple substances. The sensor in Reference 1 lacks a function to distinguish odor components in its detection unit, and therefore its odor discrimination performance for mixtures is insufficient. Reference 2 shows that by utilizing the differences in the chemical structure of conductive polymers used in the detection unit, it is possible to recognize odors as mixtures by creating differences in the response of the detection unit to various compounds through each conductive polymer. However, the chemical structures of conductive polymers are limited, making it difficult to sensitively separate the response of the detection unit to any given odor component, and thus difficult to distinguish between odors consisting of similar components. Reference 3 proposes a method in which a mixture consisting of an organic polymer, a plasticizer, and a conductive substance is used as the detection material in the detection unit, and the penetration of odor components into the organic polymer is detected as a change in the electrical resistance of the mixture. By utilizing the fact that different odor components penetrate different organic polymer compositions, it is possible to recognize odors as mixtures by using an array in which multiple detection units consisting of the above detection material containing organic polymers of different compositions are used in parallel. However, with the above-mentioned organic polymers and organic polymers containing plasticizers, even if multiple combinations of organic polymers / conductive materials are prepared, the difference in chemical properties between the organic polymers is small, resulting in insufficient odor discrimination performance. These conventional technologies cannot accurately detect, for example, real odor patterns resulting from the interaction of multiple substances or real odor patterns from substances with unknown compositions.

[0022] The present inventors have focused on the fact that the electrical conductivity of the resin composition differs depending on the amount of odor substances adsorbed onto the resin composition, and that the adsorption process to the resin composition differs for each odor substance, and have invented a resin composition and sensor element, etc., according to one embodiment of the present invention. By using such a resin composition, the odor identification performance can be improved. For example, it is possible to identify real odor patterns resulting from the interaction of multiple substances or real odor patterns caused by substances of unknown composition.

[0023] <Polyurethane resin (A)> Examples of polyurethane resin (A) include polymers consisting of a portion derived from polyol (x) and a portion derived from polyisocyanate (y), that is, polymers obtained by polymerizing polyol (x) and polyisocyanate (y).

[0024] The polyurethane resin (A) may consist of one type of polyurethane resin, or it may be a mixture of two or more types of polyurethane resins.

[0025] Examples of the polyol (x) include one or more polyols selected from the group consisting of polyoxyalkylenediol (x1) and polyester diol (x2).

[0026] The polyol (x) may consist of one type of polyol, or it may be a mixture of two or more types of polyols (x).

[0027] The polyoxyalkylenediol (x1) is preferably a polyester diol having oxyalkylene groups with 2 to 4 carbon atoms, and more preferably one or more selected from the group consisting of polyoxyethylene diol, polyoxypropylene diol, propylene oxide-ethylene oxide copolymer diol (random and / or block copolymer), and polytetramethylene ether glycol.

[0028] The number-average molecular weight of the polyoxyalkylenediol (x1) is preferably 500 to 20,000, more preferably 1,000 to 15,000, and even more preferably 2,000 to 10,000. The number-average molecular weight can be measured by the method described later.

[0029] Examples of the polyester diol (x2) include polyester diols obtained by condensing a diol selected from the group consisting of aliphatic diols and aromatic diols having 2 to 10 carbon atoms with a dicarboxylic acid selected from the group consisting of aliphatic dicarboxylic acids having 2 to 10 carbon atoms and aromatic dicarboxylic acids having 8 to 12 carbon atoms.

[0030] Examples of the aliphatic diols having 2 to 10 carbon atoms include ethylenediol, propylenediol, 1,3-propanediol, 1,4-butanediol, 1,5-pentanediol, 1,6-hexanediol, 3-methyl-1,5-pentanediol, 1,7-heptanediol, 2,2-diethyl-1,3-propanediol, 1,8-octanediol, 1,9-nonanediol, and 1,10-decanediol.

[0031] Examples of the aromatic diols include 1,4-benzenedimethanol and 1,4-benzenediethanol.

[0032] Examples of the aliphatic dicarboxylic acids having 2 to 10 carbon atoms include oxalic acid, malonic acid, succinic acid, glutaric acid, adipic acid, pimelic acid, suberic acid, azelaic acid, sebacic acid, maleic acid, and fumaric acid.

[0033] Furthermore, the aliphatic dicarboxylic acid having 2 to 10 carbon atoms may also have a ring structure. Examples of aliphatic dicarboxylic acids having the aforementioned ring structure and having 2 to 10 carbon atoms include 1,1-cyclopropanedicarboxylic acid, 1,1-cyclobutanedicarboxylic acid, 1,2-cyclohexanedicarboxylic acid, 1,3-cyclohexanedicarboxylic acid, and bicyclo[2.2.2]octane-1,4-dicarboxylic acid.

[0034] Examples of the aforementioned aromatic dicarboxylic acids having 8 to 12 carbon atoms include terephthalic acid, isophthalic acid, 1,4-naphthalenedicarboxylic acid, 2,3-naphthalenedicarboxylic acid, and 2,6-naphthalenedicarboxylic acid.

[0035] The number-average molecular weight of the polyester diol (x2) is preferably 1,000 to 20,000, more preferably 1,500 to 15,000, and even more preferably 2,000 to 10,000. The number-average molecular weight can be measured by the method described later.

[0036] Examples of the polyisocyanate (y) include aromatic polyisocyanates having 8 to 16 carbon atoms, linear aliphatic polyisocyanates having 5 to 12 carbon atoms, and alicyclic polyisocyanates having 9 to 15 carbon atoms. These polyisocyanates may have 2 to 3 or more isocyanate groups.

[0037] The polyisocyanate (y) may consist of one type of polyisocyanate, or it may be a mixture of two or more types of polyisocyanates.

[0038] Examples of the aforementioned aromatic polyisocyanates having 8 to 16 carbon atoms include 2,6-tolylene diisocyanate, 2,4'-diphenylmethane diisocyanate, 1,3-phenylene diisocyanate, 1,4-phenylene diisocyanate, 2,4-tolylene diisocyanate, crude tolylene diisocyanate, 4,4'-diphenylmethane diisocyanate, crude diphenylmethane diisocyanate, m-xylylene diisocyanate, 4,4'-diisocyanatobiphenyl, 4,4'-diisocyanato-3,3'-dimethylbiphenyl, and 1,5-diisocyanatonaphthalene. For example, when measuring odor from wastewater, a polyurethane resin (A) composed of aromatic polyisocyanates may be used.

[0039] Examples of the chain-like aliphatic polyisocyanates having 5 to 12 carbon atoms include pentamethylene diisocyanate, hexamethylene diisocyanate, and trimethylhexamethylene diisocyanate (a mixture of 2,2,4- and 2,4,4-).

[0040] Examples of the alicyclic polyisocyanates having 9 to 15 carbon atoms include isophorone diisocyanate, dicyclohexylmethane-4,4'-diisocyanate, 1,4-bis(isocyanatomethyl)cyclohexane, and norbornane diisocyanate.

[0041] In the polyurethane resin (A) described above, the molar ratio (polyol(x) / polyisocyanate(y)) of the number of moles of polyol(x) and the number of moles of polyisocyanate(y), calculated based on the number-average molecular weight, is preferably 1.0 to 1.1, and more preferably 1.0 to 1.05.

[0042] The number-average molecular weight of the polyurethane resin (A) is preferably 10,000 to 300,000, more preferably 15,000 to 250,000, and even more preferably 20,000 to 200,000. The number-average molecular weight can be measured by the method described later.

[0043] <Measurement conditions for number-average molecular weight> In this specification, the number-average molecular weight is not particularly limited, but can be measured, for example, using gel permeation chromatography (GPC) under the following conditions. As the sample to be subjected to GPC, for example, a filtrate obtained by dissolving the target material, such as polyurethane resin (A), polyoxyalkylenediol (x1), and polyester diol (x2), in a suitable solvent, and then filtering the resulting solution through a glass filter, can be used. Examples of solvents for dissolving polyurethane resin (A) include dimethylformamide (DMF). Examples of solvents for dissolving polyoxyalkylenediol (x1) include tetrahydrofuran (THF). Examples of solvents for dissolving polyester diol (x2) include tetrahydrofuran (THF).

[0044] Equipment (example): HLC-8120 manufactured by Tosoh Corporation Examples of columns: One Guardcolumn α (manufactured by Tosoh Corporation) and one TSK GEL α-M (manufactured by Tosoh Corporation) linked together; two TSK GEL GMH6 (manufactured by Tosoh Corporation); or one TSK GEL SuperH3000 (manufactured by Tosoh Corporation) and one TSK GEL SuperH4000 (manufactured by Tosoh Corporation) linked together. Measurement temperature: 40℃ Sample solution: 0.25% by weight solution Solution injection volume: 100μl Detection device: Refractive index detector Furthermore, a calibration curve for calculating the number-average molecular weight can be created using the least squares method based on 12 measured number-average molecular weights obtained using 12 types of standard polystyrene (TSKstandard POLYSTYRENE, manufactured by Tosoh Corporation) each having a different number-average molecular weight (500, 1050, 2800, 5970, 9100, 18100, 37900, 96400, 190000, 355000, 1090000, or 2890000) as reference materials.

[0045] The polyester diol (x2) can be obtained, for example, by a known manufacturing method. Specifically, a method can be described in which a polyol, a polycarboxylic acid, and a polymerization catalyst are placed in a reaction vessel equipped with a stirring device, a temperature control device, and a nitrogen inlet tube, and the polyol and polycarboxylic acid are reacted for 4 hours at a predetermined temperature under a nitrogen stream while distilling off the water produced, and then the reaction is carried out for another hour under reduced pressure of 5 to 20 mmHg to obtain the polyester diol (x2). Examples of the polymerization catalyst include tetraisopropoxytitanium. The predetermined temperature is not particularly limited, but for example, it may be 200°C.

[0046] The polyurethane resin (A) can be obtained, for example, by known manufacturing methods. Specifically, a method including the steps shown in (1) to (3) below can be cited.

[0047] (1) A step of reacting the polyol (x) and polyisocyanate (y) as constituent monomers, along with a reaction solvent and reaction catalyst as needed, into a reaction vessel equipped with a condenser, a stirrer and a nitrogen inlet tube, and stirring at a predetermined temperature, for example, about 65°C, at a predetermined time, for example, 10 hours, under atmospheric pressure and a nitrogen atmosphere, to a reaction of the polyol (x) and the polyisocyanate (y). Here, the polyol (x) may contain polyoxyalkylenediol (x1) and / or polyester diol (x2).

[0048] (2) After step (1), a reaction stopper and, if necessary, a chain extender are added dropwise to the inside of the reaction vessel, and stirring is continued for another hour.

[0049] (3) After step (2), a step of obtaining polyurethane resin (A) diluted to a desired concentration from the reaction vessel.

[0050] The reaction solvent can be any commonly used aprotic solvent without any particular limitations. Examples of such reaction solvents include dimethylformamide (DMF), N-methylpyrrolidone (NMP), toluene, xylene, tetrahydrofuran (THF), and methyl ethyl ketone (MEK).

[0051] As the reaction catalyst, catalysts commonly used in urethane reactions can be used. For example, amine catalysts (triethylamine, N-ethylmorpholine, triethylenediamine (DABCO), etc.), tin catalysts (dibutyltin dilaurate, dioctyltin dilaurate, tin octoate, etc.), and titanium catalysts (tetrabutyl titanate, etc.) can be used. The amount of the reaction catalyst used is 0.1% by weight or less relative to the weight of the resulting polyurethane resin (A).

[0052] The reaction temperature is suitable to be a temperature that can normally be used in a urethane reaction, for example, 20 to 140°C, and preferably in the range of 40 to 100°C from the viewpoint of controlling the reaction time within a suitable range.

[0053] A chain extender (P) may also be used in the production of the polyurethane resin (A).

[0054] Examples of chain extenders (P) used in the production of polyurethane resin according to one embodiment of the present invention include polyamines (P1) as essential components and polyols (P2) as optional components. One type of chain extender (P) may be used alone, or two or more types may be used in combination.

[0055] Examples of polyamines (P1) include diamines having 2 to 12 carbon atoms (ethylenediamine, propylenediamine, hexamethylenediamine, isophoronediamine, toluenediamine, and piperazine, etc.), poly(n=2-6)alkylene(2-6 carbon atoms) poly(n=3-7)amines (diethylenetriamine, dipropylenetriamine, dihexylentriamine, triethylenetetramine, tetraethylenepentamine, pentaethylenehexamine, and hexaethyleneheptamine, etc.), and hydrazine or its derivatives (dibasic acid dihydrazides, such as adipic acid dihydrazide, etc.).

[0056] Examples of polyols (P2) include diols with a manganese content of less than 500, such as aliphatic dihydric alcohols with 2 to 8 carbon atoms [linear diols (ethylene glycol, diethylene glycol, 1,3-propanediol, 1,4-butanediol, 1,5-pentanediol, and 1,6-hexanediol, etc.) and diols with branched alkyl chains (1,2-propanediol, neopentyl glycol, 3-methyl-1,5-pentanediol, 2,2-diethyl-1,3-propanediol, 1,2-, 1,3- or 2,3-butanediol, etc.)]; and alicyclic group-containing diols with 6 to 10 carbon atoms. Examples include hydric alcohols [such as 1,4-bis(hydroxymethyl)cyclohexane and 2,2-bis(4-hydroxycyclohexyl)propane]; dihydric alcohols containing aromatic rings with 8 to 20 carbon atoms [m- or p-xylylene glycol, bis(hydroxyethyl)benzene, bis(hydroxyethoxy)benzene]; alkylene oxide (hereinafter abbreviated as "AO") adducts of bisphenols (such as bisphenol A, bisphenol S, and bisphenol F) with 2 to 12 carbon atoms, AO adducts of dihydroxynaphthalene, and bis(2-hydroxyethyl)terephthalate]. Diols with Mn less than 500 may be used alone or in combination of two or more.

[0057] In the production of polyurethane resin (A), a reaction stopper (Q) may be used to adjust the molecular weight of the polyurethane resin.

[0058] Examples of reaction stoppers (Q) include monoalcohols having 1 to 10 carbon atoms (methanol, propanol, butanol, and 2-ethylhexanol, etc.) and monoamines having 2 to 8 carbon atoms [mono or dialkylamines having 2 to 8 carbon atoms (n-butylamine and di-n-butylamine, etc.), mono or dialkanolamines having 2 to 6 carbon atoms (monoethanolamine, diethanolamine, and propanolamine, etc.)]. Of these, mono or dialkanolamines having 2 to 6 carbon atoms are preferred. Reaction stoppers (Q) may be used alone or in combination of two or more.

[0059] <Surfactant (B)> A resin composition according to one embodiment of the present invention may contain a surfactant (B) as described below. Surfactant (B) acts as a dispersant for the conductive carbon material (C) described later. Surfactant (B) can be appropriately selected from known surfactants within the range in which it exhibits the above-described effect.

[0060] The surfactant (B) is not particularly limited, but it is preferably having an HLB value of 8 to 18, more preferably 9 to 17, and most preferably 10 to 16. By using a surfactant (B) with such an HLB value, good odor discrimination performance can be obtained.

[0061] The "HLB value" used here is an index that indicates the balance between hydrophilicity and lipophilicity, and is known as the value calculated by the Oda method, as described on page 212 of "Introduction to Surfactants" [published by Sanyo Chemical Industries, Ltd. in 2007, written by Takehiko Fujimoto], and not a value calculated by the Griffin method.

[0062] The HLB value can be calculated from the ratio of the organic to inorganic values ​​of an organic compound.

[0063] HLB=10×Inorganic / Organic Here, the inorganic and organic values ​​in the above formula represent index values ​​for expressing organic and inorganic properties proposed by Fujita et al., and can be calculated using the values ​​in the table on page 213 of the aforementioned "Introduction to Surfactants".

[0064] Examples of surfactants (B) include anionic surfactants, cationic surfactants, amphoteric surfactants, and nonionic surfactants.

[0065] Examples of anionic surfactants include alkali metal salts of carboxylic acids having 10 to 24 carbon atoms and alkali metal salts of alkyl sulfonic acids having 14 to 24 carbon atoms.

[0066] Examples of the carboxylic acids having 10 to 24 carbon atoms include decanoic acid, undecanoic acid, dodecanoic acid, tridecanoic acid, tetradecanoic acid, hexadecanoic acid, heptadecanoic acid, octadecanoic acid, pentadecanoic acid, nonadecanoic acid, eicosanic acid, henicosanoic acid, docosanic acid, tricosanic acid, and tetracosanic acid.

[0067] Examples of alkyl groups in the C14-C24 alkylsulfonic acid include tetradecyl, pentadecyl, hexadecyl, heptadecyl, octadecyl, nonadecyl, icosyl, henicosyl, docosyl, tricosyl, and tetracosyl groups.

[0068] Examples of alkali metals included in the alkali metal salt include sodium and potassium.

[0069] Examples of cationic surfactants include quaternary ammonium halide salts having an alkyl group with 12 to 24 carbon atoms.

[0070] Examples of quaternary ammonium compounds having an alkyl group with 12 to 24 carbon atoms include tetrapropylammonium, tetrabutylammonium, tetrapentylammonium, tetrahexylammonium, dimethyldioctylammonium, didecyldimethylammonium, decyltrimethylammonium, dodecyltrimethylammonium, tridecyltrimethylammonium, hexadecyltrimethylammonium, methyltrioctylammonium, octyltrimethylammonium, tributylmethylammonium, octadecyltrimethylammonium, tetradecyltrimethylammonium, nonadecyltrimethylammonium, icosyltrimethylammonium, henicosyltrimethylammonium, heptadecyltrimethylammonium, and pentadecyltrimethylammonium.

[0071] Examples of the aforementioned halide salts include fluoride salts, chloride salts, bromide salts, and iodide salts.

[0072] Examples of amphoteric surfactants include dimethyl(3-sulfopropyl)ammonium intramolecular salt having an alkyl group with 10 to 22 carbon atoms, and N-alkyl-N,N-dimethylglycine having an alkyl group with 10 to 22 carbon atoms.

[0073] Examples of dimethyl(3-sulfopropyl)ammonium hydroxide intramolecular salts having an alkyl group with 10 to 22 carbon atoms include decyldimethyl(3-sulfopropyl)ammonium hydroxide intramolecular salt, undecyldimethyl(3-sulfopropyl)ammonium hydroxide intramolecular salt, dodecyldimethyl(3-sulfopropyl)ammonium hydroxide intramolecular salt, tridecyldimethyl(3-sulfopropyl)ammonium hydroxide intramolecular salt, tetradecyldimethyl(3-sulfopropyl)ammonium hydroxide intramolecular salt, and pentadecyldimethyl(3-sulfopropyl)ammonium hydroxide intramolecular salt. Examples include intramolecular salts, hexadecyldimethyl(3-sulfopropyl)ammonium hydroxide intramolecular salt, heptadecyldimethyl(3-sulfopropyl)ammonium hydroxide intramolecular salt, octadecyldimethyl(3-sulfopropyl)ammonium hydroxide intramolecular salt, nonadecyldimethyl(3-sulfopropyl)ammonium hydroxide intramolecular salt, icosyldimethyl(3-sulfopropyl)ammonium hydroxide intramolecular salt, henicosyldimethyl(3-sulfopropyl)ammonium hydroxide intramolecular salt, and docosyldimethyl(3-sulfopropyl)ammonium hydroxide intramolecular salt.

[0074] Examples of N-alkyl-N,N-dimethylglycine having an alkyl group with 10 to 22 carbon atoms include N-dodecyl-N,N-dimethylglycine and N-octadecyl-N,N-dimethylglycine.

[0075] Examples of nonionic surfactants include higher alcohol ethylene oxide adducts.

[0076] Examples of higher alcohols include 1-hexyl alcohol, 1-heptyl alcohol, 1-octyl alcohol, 1-nonyl alcohol, 1-decyl alcohol, 1-undecyl alcohol, 1-dodecyl alcohol, 1-tridecyl alcohol, 1-tetradecyl alcohol, 1-pentadecyl alcohol, 1-hexadecyl alcohol, 1-heptadecyl alcohol, and 1-octadecyl alcohol.

[0077] The number of moles of ethylene oxide added is preferably 5 to 50, more preferably 5 to 40, and even more preferably 5 to 30, from the viewpoint of odor discrimination performance.

[0078] The weight ratio [(A) / (B)] of the polyurethane resin (A) to the surfactant (B) is preferably 1.0 to 4.0, more preferably 1.0 to 2.3, and most preferably 1.0 to 1.5, from the viewpoint of odor identification performance.

[0079] The polyurethane resin (A) and the surfactant (B) may or may not be miscible.

[0080] From the viewpoint of dispersibility in the conductive carbon material (C), surfactant (B) is preferably a nonionic surfactant. Furthermore, from the viewpoint of dispersibility in the conductive carbon material (C), surfactant (B) is preferably having at least one of an amide group, a primary amino group, a secondary amino group, or a tertiary amino group. Furthermore, from the viewpoint of dispersibility in the conductive carbon material (C), surfactant (B) is preferably having at least one of an oxyethylene chain, an oxypropylene chain, and a random or block structure of oxyethylene-oxypropylene. The random structure of oxyethylene-oxypropylene is a chain-like structure in which both oxyethylene and oxypropylene are irregularly linked. The block structure of oxyethylene-oxypropylene is a chain-like structure in which oxyethylene blocks, in which oxyethylene is linked, and oxypropylene blocks, in which oxypropylene is linked, are linked.

[0081] <Conductive carbon material (C)> In this specification, conductive carbon material (C) refers to a carbon material with a volume resistivity of 0.1 Ω·cm or less. The resin composition described above is a state in which conductive carbon material (C) is dispersed in a mixture of polyurethane resin (A) and surfactant (B). The resin composition becomes conductive when the conductive carbon material (C) particles come into contact with each other and form conductive paths.

[0082] Examples of conductive carbon materials (C) include carbon black, carbon nanotubes, and graphene.

[0083] Commercially available carbon black products include Ketjenblack EC (product name from Akzo, Netherlands), Ketjenblack EC-300J (product name from Lion Specialty Chemicals Co., Ltd.), Ketjenblack EC-600JD (product name from Lion Specialty Chemicals Co., Ltd.), Seast G116, 116 (product names from Tokai Carbon Co., Ltd.), Nitelon #10 (product name from Nippon Steel Chemical Co., Ltd.), Denka Black (product name from Denki Kagaku Kogyo Co., Ltd.), and SUPER C-65 (product name from MTI Corporation, USA).

[0084] Commercially available carbon nanotubes include VGCF-H (various product names from Showa Denko Corporation), among others.

[0085] Sigma-Aldrich is one company that manufactures commercially available graphene.

[0086] The shape of the conductive carbon material (C) is preferably fibrous or spherical.

[0087] If the material is fibrous, the fiber diameter is preferably 0.1 to 10 μm, and more preferably 0.1 to 5 μm. The fiber length is preferably 0.1 to 10 μm, and more preferably 1 to 10 μm.

[0088] When the particles are spherical, the primary particle diameter is preferably 10 nm to 200 nm, and more preferably 20 nm to 150 nm.

[0089] Furthermore, from the viewpoint of conductivity in the resin composition and sensor sensitivity, the conductive carbon material preferably has a primary particle diameter of 100 nm or less. The particle diameter of the conductive carbon material can be determined by known methods. For example, the particle diameter of the conductive carbon material can be observed with a transmission electron microscope (TEM) and measured by image analysis using an image processing device (e.g., Keyence's VHX-700F digital microscope). If the conductive carbon material is a known or commercially available product, the particle diameter may be a literature value or a catalog value.

[0090] From the viewpoint of keeping the measurement time short and keeping the measurement error small to obtain a good accuracy, the content of the conductive carbon material (C) is preferably 25 to 75% by weight, more preferably 30 to 65% by weight, and most preferably 35 to 55% by weight, based on 100% by weight of the total of the polyurethane resin (A), surfactant (B), and conductive carbon material (C). Alternatively, from the viewpoint of sensitivity for receiving odor substances, the content of the conductive carbon material (C) may be 5 to 30% by weight, 5 to 20% by weight, or 5 to 10% by weight, based on 100% by weight of the total of the polyurethane resin (A), surfactant (B), and conductive carbon material (C).

[0091] The resin composition may further contain other components besides the polyurethane resin (A), surfactant (B), and conductive carbon material (C) described above, to the extent that the effects of the present invention are obtained. Examples of other components include solvents (D). These other components can be suitably used to the extent that both the effects of the present invention and the effects of the other components are obtained.

[0092] The solvent (D) can be incorporated into the resin composition from the viewpoint of improving the compatibility between the polyurethane resin (A) and the surfactant (B), improving the dispersibility of the conductive carbon material (C) in the resin composition, or improving the coatability of the resin composition. Examples of solvent (D) include N-methyl-2-pyrrolidone, propylene glycol monomethyl ether acetate, ethyl butyrate, butyl butyrate, ethyl acetate, N,N-dimethylformamide, N,N-dimethylacetamide, toluene, and xylene.

[0093] The content of solvent (D) in the resin composition can be appropriately determined from the above viewpoint. For example, from the viewpoint of coating properties, the content of solvent (D) in the resin composition is preferably 100 to 10,000 parts by weight per 100 parts by weight of the total of polyurethane resin (A), surfactant (B), and conductive carbon material (C).

[0094] <Method for producing resin compositions> A specific example of a method for producing a resin composition according to one embodiment of the present invention is as follows.

[0095] The resin composition is obtained as a slurry by mixing a polyurethane resin (A), a surfactant (B), a conductive carbon material (C), and optionally a solvent (D), and kneading them uniformly in a stirrer. When solvent (D) is added, the solvent (D) is removed from the resin composition by distillation. The solvent (D) may be removed by distillation from the resin composition produced by uniform mixing, or it may be removed by distillation from the coating film produced during the manufacture of the sensor element described later.

[0096] The solvent (D) is not particularly limited as long as it is a medium that can be removed by drying, but preferred examples include N-methylpyrrolidone, N,N-dimethylformamide, N,N-dimethylacetamide, ethylene acetate, water, toluene, and xylene.

[0097] [2. Sensor element 31] The aforementioned resin composition exhibits different changes in electrical conductivity over time depending on whether odor substance A is adsorbed or odor substance B, which is different from odor substance A, is adsorbed. By utilizing this property, a sensor element 31 capable of detecting and identifying odor substances can be realized.

[0098] The following describes the overview and effects of a sensor element 31 to which a resin composition according to one embodiment of the present invention is applied.

[0099] The sensor element 31 comprises an odor substance receiving layer 315 containing the above-mentioned resin composition, a first metal wiring 313A, and a second metal wiring 313B. In the following, when the first metal wiring 313A and the second metal wiring 313B are not distinguished, they may be referred to simply as metal wiring 313.

[0100] Here, the first metal wiring 313A and the second metal wiring 313B will be explained using Figures 2 and 3. Figure 2 is a top view showing an example of the configuration of the sensor element 31, and Figure 3 is a cross-sectional view showing an example of the configuration of the sensor element 31 shown in Figure 2.

[0101] The first metal wiring 313A and the second metal wiring 313B are metal wirings that function as electrodes for measuring changes in the electrical conductivity of the odor substance receiving layer 315 (i.e., the resin composition). That is, the first metal wiring 313A and the second metal wiring 313B are spaced apart from each other, and the odor substance receiving layer 315 is in contact with at least a portion of the first metal wiring and at least a portion of the second metal wiring. In one example, the first metal wiring 313A and the second metal wiring 313B are metal wirings that are not in direct contact with each other, and may be substantially parallel to each other, as shown in Figure 2.

[0102] As shown in Figure 2, the metal wiring 313, including the first metal wiring 313A and the second metal wiring 313B, may be arranged on a substrate 311. The substrate 311 may be a substrate such as glass epoxy, which is commonly used in electronic circuits. The metal wiring 313 may be a metal wiring such as copper or gold. The thickness of the first metal wiring 313A and the second metal wiring 313B, as viewed from a direction perpendicular to the surface of the substrate, is preferably 10 μm to 2 mm, and more preferably 10 μm to 1 mm. The height, i.e., thickness, of the first metal wiring 313A and the second metal wiring 313B, as viewed from a direction parallel to the surface of the substrate, is preferably 1 μm to 100 μm, and more preferably 10 μm to 50 μm. The spacing between the first metal wiring 313A and the second metal wiring 313B is preferably 1 μm to 3 mm, and more preferably 1 μm to 1.5 mm. The length of the metal wiring 313 is preferably 100 μm to 50 mm, and more preferably 500 μm to 30 mm.

[0103] The metal wiring 313 may be placed on the sealing substrate 312. Figure 3 shows cross-section AA of Figure 2. As shown in Figure 3, the sealing substrate 312 may be placed on a substrate 311 made of glass epoxy or the like, and the metal wiring 313 may be placed on the sealing substrate 312. Vinyl tape 314 may be used to fix the sealing substrate 312 to the substrate 311. The vinyl tape 314 may also be used to adjust the length of the exposed portion of the metal wiring 313 by masking the excess portion of the metal wiring 313. Here, the exposed portion of the metal wiring 313 is the portion in contact with the odor substance receiving layer 315. The vinyl tape 314 may also serve as an insulator for adjusting the length of the portion in contact with the metal wiring 313 and the odor substance receiving layer 315.

[0104] The odor substance receiving layer 315 may be in contact with at least a portion of the first metal wiring 313A and at least a portion of the second metal wiring 313B. The odor substance receiving layer 315 may be arranged to fill the region sandwiched between the first metal wiring 313A and the second metal wiring 313B, for example, as shown in Figures 2 and 3.

[0105] The odor substance receiving layer 315 may be in contact with at least a portion of the first metal wiring 313A and at least a portion of the second metal wiring 313B. The odor substance receiving layer 315 may be arranged to fill the region sandwiched between the first metal wiring 313A and the second metal wiring 313B, for example, as shown in Figures 2 and 3.

[0106] If the electrical conductivity of the odor substance receiving layer 315 (i.e., the electrical conductivity of the sensor element 31) is low, it is desirable that the distance between the first metal wiring 313A and the second metal wiring 313B be less than or equal to a predetermined distance (for example, 500 μm).

[0107] The sensor element 31 can detect and identify various odor substances by applying a resin composition in which the change in electrical conductivity over time differs depending on whether odor substance A is adsorbed or odor substance B, which is different from odor substance A, is adsorbed. In the odor sensor 30 described later, multiple sensor elements 31 may be arranged, each having a substrate 311 equipped with a configuration for detecting odor substances (metal wiring 313 and odor substance receiving layer 315). Multiple sets of odor substance receiving layers 315 with the same composition may be arranged on each substrate 311. When multiple sensor elements 31 are arranged, each sensor element 31 is provided with a constant voltage power supply and a voltmeter. In the odor sensor 30, one configuration for detecting odor substances (metal wiring 313 and odor substance receiving layer 315) may be arranged on each substrate 311. Alternatively, in the odor sensor 30, multiple sets of configurations for detecting odor substances (metal wiring 313 and odor substance receiving layer 315) may be arranged on a single substrate 311. In the latter case, a constant voltage power supply and a voltmeter are connected to each of the sets provided on the circuit board 311.

[0108] The composition of each of the multiple odor substance receiving layers 315 in the odor sensor 30 may be the same or different. If the odor sensor 30 includes odor substance receiving layers 315 with the same composition, the same odor substance can be detected in each of the multiple odor substance receiving layers 315. If the odor sensor 30 includes odor substance receiving layers 315 with different compositions, each of the multiple odor substance receiving layers 315 will respond differently to the odor substance. In this way, by providing multiple sets of configurations for detecting odor substances, the accuracy of odor substance identification in the odor sensor 30 can be improved.

[0109] [3. Odor Sensor 30] The following describes the overview and effects of the odor sensor 30 to which the sensor element 31 is applied, using Figure 4. Figure 4 is a block diagram showing an example of the configuration of the odor sensor 30 to which the sensor element 31 is applied. Note that in the sensor element 31 shown in Figure 1, the vinyl tape 314 is omitted from the illustration for simplification.

[0110] The odor sensor 30 includes a sensor element 31 for detecting odor substances, a constant voltage power supply 32 (power supply), and a voltmeter 33 (measuring instrument).

[0111] The first metal wiring 313A and the second metal wiring 313B of the sensor element 31 are connected by a lead wire W. Figure 4 shows an example in which a constant voltage power supply 32 and a voltmeter 33 are connected to the lead wire W.

[0112] The constant voltage power supply 32 is a power source for supplying power to the sensor element 31. The constant current source 32 supplies a constant voltage to the sensor element 31 via lead wires. The voltage value supplied by the constant voltage power supply 32 is 0.5V to 10V, for example, 2.5V or 5.0V.

[0113] The voltmeter 33 measures the potential difference that occurs between the first metal wiring 313A and the second metal wiring 313B when a constant voltage supplied from the constant voltage power supply 32 is supplied to the odor substance receiving layer 315.

[0114] Furthermore, the odor sensor 30 is equipped with an amplifier (not shown) in the circuit for measuring odor substances, prior to the voltmeter 33, and this amplifier amplifies the acquired signal and supplies it to the voltmeter 33.

[0115] Furthermore, the odor sensor 30 is equipped with a reference circuit in addition to the circuit for measuring odor substances, and the voltmeter 33 acquires the difference (potential difference) between the value obtained in the odor substance measurement circuit and the value obtained in the reference circuit as a voltage value.

[0116] The odor sensor 30 may also be further equipped with a housing 34, although this is not a mandatory configuration. The housing 34 is a container capable of enclosing air containing odor substances. If a housing 34 is provided, the sensor element 31 is installed inside the housing 34.

[0117] The housing 34 is equipped with an inlet 341 for introducing odor substances and an outlet 342 for discharging air containing odor substances. The introduction of odor substances may be performed by inserting filter paper or the like soaked in odor substances into the housing 34 through the inlet 341, or by introducing air containing odor substances into the housing 34 through the inlet 341. The housing 34 is a container for enclosing air containing odor substances at a predetermined concentration (e.g., 200 ppm) or higher.

[0118] Although not mandatory, an airflow generating fan 35 may be provided at the exhaust port 342 of the housing 34. The airflow generating fan 35 is used to create airflow inside the housing 34 or to expel the gas inside the housing 34 to the outside of the housing 34 through the exhaust port 342.

[0119] The odor sensor 30 may also be equipped with a constant current source (power supply) (not shown) as a substitute for the constant voltage power supply 32, and an ammeter (measuring instrument) (not shown) as a substitute for the voltmeter 33. In this case, the constant current source functions as a power supply for supplying power to the sensor element 31, applying a constant current to the sensor element 31 via lead wires. The ammeter, on the other hand, measures the current flowing between the first metal wiring 313A and the second metal wiring 313B when a constant voltage is applied to the odor substance receiving layer 315. Both the first metal wiring 313A and the second metal wiring 313B can function as electrodes. Hereinafter, when the metal wiring 313 functions as an electrode, it may be referred to as "electrode 313".

[0120] The odor sensor 30 outputs a measurement value that shows the change in the electrical conductivity of the sensor element 31 over time, before and after odor substances are adsorbed onto the sensor element 31. This makes it possible to detect and identify various odor substances.

[0121] [4. Odor measuring device 100] The odor sensor 30 described above can output the change in the electrical conductivity of the sensor element 31 over time for each odor substance when various odor substances are adsorbed onto the sensor element 31. By applying this odor sensor 30, it is possible to compare the change in the electrical conductivity of the sensor element 31 over time when odor substance A is adsorbed onto the sensor element 31 with the change in the electrical conductivity of the sensor element 31 over time when odor substance B is adsorbed onto the sensor element 31. Based on such comparison results, an odor measuring device 100 can be realized that can estimate the odor substances adsorbed onto the sensor element 31.

[0122] Furthermore, the odor measuring device 100 can perform highly accurate estimation of odor substances by using an estimation model 22 generated by machine learning. The estimation model 22 can be generated using training data that includes a combination of measurement values ​​obtained when each of several odor substances is adsorbed onto at least one sensor element 31, and identification information specific to the odor substance to which the measurement value was obtained.

[0123] The following describes the overview and effects of the odor measuring device 100 to which the odor sensor 30 is applied. The odor measuring device 100 is a device that estimates odor substances adsorbed on the sensor element 31 from the change in electrical conductivity that occurs in the sensor element 31 to which the above-mentioned resin composition is applied.

[0124] The odor measuring device 100 of this embodiment separately comprises a sensor chamber 60 equipped with a plurality of sensor elements 31A (hereinafter also referred to as "sensor element group 31A") and a target sample receiving section 50 into which a target sample containing odor substances is introduced and which contains a gas containing odor substances generated from the target sample. In this embodiment, each sensor element 31 included in the sensor element group 31A is simply referred to as "sensor element 31".

[0125] The odor measuring device 100 of this embodiment employs a configuration in which the gas containing the odor substance inside the target sample receiving section 50 is pushed towards the sensor chamber 60 using another gas (carrier gas). In this embodiment, the gas inside the target sample receiving section 50 when the target sample is introduced into the target sample receiving section 50 (i.e., the gas containing the odor substance to be detected) is referred to as the first gas. On the other hand, the carrier gas used to push the first gas towards the sensor chamber 60 is referred to as the second gas.

[0126] Figure 1 is a schematic diagram of the odor measuring device 100. As shown in Figure 1, the odor measuring device 100 comprises an odor sensor 30, a target sample receiving section 50, a sensor chamber 60, a gas supply section 80, and an estimation device 10. The odor measuring device 100 may also further include a control section 51. Furthermore, the odor measuring device 100 may further include an estimation device 10a.

[0127] Figure 1 shows an example in which gas flows from the gas supply unit 80 to the target sample receiving unit 50 and then to the sensor chamber 60. The gas supply unit 80, the target sample receiving unit 50, and the sensor chamber 60 are connected by pipes.

[0128] [Target sample receiving section 50] The sample receiving section 50 is capable of receiving a sample containing odor substances and holding the first gas. The sample receiving section 50 includes a first port 501 through which the second gas entering the interior passes, and a second port 502 through which the first gas and second gas exiting the interior can pass. In Figure 1, the first port 501 is shown to be located at the top of the page of the sample receiving section 50, and the second port 502 is shown to be located at the bottom of the page of the sample receiving section 50, but it is not limited to this configuration. For example, the positions of the first port 501 and the second port 502 can be appropriately set depending on the type and combination of odor components contained in the first gas. For example, the positions of the first port 501 and the second port 502 may be changed depending on whether the weight per unit volume (i.e., specific gravity) of the odor components contained in the first gas is heavier or lighter than that of the second gas. Furthermore, the sample receiving section 50 may also be equipped with an airflow generating fan 35 inside, as shown in Figure 4.

[0129] The sample receiving section 50 is equipped with a sample inlet 503 for receiving a liquid or solid sample. The sample receiving section 50 may also be equipped with a placement section (not shown) for placing the sample. If the sample is liquid, the placement section may be a cup for holding the liquid, and if the sample is solid, the placement section may be a petri dish in which the solid is placed. The sample may be introduced into the sample receiving section 50 in a gaseous state as a first gas from the sample inlet 503. In this way, because the sample receiving section 50 is capable of receiving a liquid or solid sample, it is possible to adjust the concentration of odorants in the first gas. For example, even with the same odorant, it is easy to adjust the level of concentration of the odorant in the first gas.

[0130] The inner surface of the sample receiving section 50 may be made of a material that is inert to odor substances. A material that is inert to odor substances is a material that does not significantly change the concentration of each odor substance contained in the gas sent to the sensor chamber 60. For example, a material that is inert to odor substances is a material that odor substances do not easily adsorb or dissolve into. Examples of materials that are inert to odor substances include glass, metal, and resin. When using metal, stainless steel (SUS) is preferred, and when using resin, fluororesin, polypropylene (PP), polyethylene (PE), ABS resin, and polyethylene terephthalate (PET) are preferred.

[0131] If the inner surface of the sample receiving section 50 is made of a material that adsorbs odor substances contained in the first gas, odor substances may be adsorbed onto each part, potentially affecting subsequent measurements.

[0132] Because the inner surface of the sample receiving section 50 is made of a material that is inert to odor substances, the risk of the inner surface material reacting with the odor substances contained in the first gas, or of odor substances being adsorbed onto the inner surface, is reduced. Therefore, the risk of the odor substances contained in the first gas supplied to the sensor chamber 60 changing while they are contained within the sample receiving section 50, or of the concentration of odor substances becoming diluted, is reduced.

[0133] The odor measuring device 100, by including a sample receiving section 50, can equalize the concentration of the first gas within the sample receiving section 50 before sending the first gas to the sensor chamber 60, even if the target sample is a liquid or solid. Furthermore, the odor measuring device 100, by including a sample receiving section 50, can push the first gas into the sensor chamber 60 at a constant flow rate. As a result, even when measurements are repeated, the odor measuring device 100 can send the first gas to the sensor chamber 60 under the same conditions each time, enabling stable and repeated measurements.

[0134] The volume of the sample receiving section 50 is preferably 1 to 200 times the volume of the sensor chamber 60. In particular, it is preferable that the volume of the sample receiving section 50 is larger than the volume of the sensor chamber 60. More preferably, the volume of the sample receiving section 50 is 2 times or more the volume of the sensor chamber 60, and even more preferably 4 times or more. Furthermore, it is preferable that the volume of the sample receiving section 50 is 100 times or less the volume of the sensor chamber 60, and even more preferably 60 times or less. By having a volume of the sample receiving section 50 that is 1 or more times the volume of the sensor chamber 60, the concentration of odor substances in the sensor chamber 60 is appropriately adjusted, and the measurement results from the sensor in the sensor chamber 60 are stably output. In addition, by having a volume of the sample receiving section 50 that is 200 times or less the volume of the sensor chamber 60, it is easier to adjust the temperature and humidity inside the sample receiving section 50, so that the measurement results from the sensor are stably output, and the size of the odor measuring device 100 can be made compact.

[0135] If the volume of the sample receiving section 50 is less than one times the volume of the sensor chamber 60, odor substances generated in the sample receiving section 50 may be diluted in the sensor chamber 60, potentially reducing the measurement sensitivity of the sensor. Furthermore, if the volume of the sample receiving section 50 is greater than 200 times the volume of the sensor chamber 60, the volume of the sample receiving section 50 is too large, which may reduce the uniformity of the concentration, temperature, and humidity of the first gas, making it impossible to repeatedly supply the first gas to the sensor chamber 60 under the same conditions. Additionally, the overall size of the odor measuring device 100 may increase.

[0136] Figure 1 shows an example where the volume inside the target sample receiving section 50 is eight times the volume inside the sensor chamber 60.

[0137] For example, if the inner surface of the tube 93 is made of a material that adsorbs odor substances contained in the first gas, odor substances may be adsorbed on various parts, potentially affecting subsequent measurements. Therefore, it is preferable that the inner surface of the tube 93, which guides the first gas from the sample receiving section 50 to the sensor chamber 60, be made of a material that is inert to odor substances, similar to the inner surface of the sample receiving section 50. Examples of materials that are inert to odor substances include glass, metal, and resin. When using metal, stainless steel (SUS) is preferred, and when using resin, fluororesin, polypropylene (PP), polyethylene (PE), ABS resin, and polyethylene terephthalate (PET) are preferred.

[0138] The sample receiving section 50 may be configured to be detachable from the tubes 92 and 93. As described above, because the target sample receiving section 50 is detachable, when the previous measurement is completed and the next measurement is to be performed, a new target sample receiving section 50 can be attached without purging the inside of the target sample receiving section 50. This allows the odor measuring device 100 to perform multiple measurements in a short amount of time.

[0139] Furthermore, because the sample receiving section 50 is detachable, the sample receiving section 50 into which the sample has been introduced can be maintained at a desired temperature using a separate insulated chamber from the odor measuring device 100. This means that, for example, even if the adjustment section 51 described later cannot be provided in the odor measuring device 100, the odor measuring device 100 can adjust the temperature of the sample receiving section 50.

[0140] [Adjustment section 51] The adjustment unit 51 adjusts at least one of the temperature and humidity of the first gas contained within the target sample receiving unit 50. When the adjustment unit 51 adjusts the temperature, it is, for example, a heater or a cooler. In this case, the adjustment unit 51 may be configured to cover the entire target sample receiving unit 50. When the adjustment unit 51 adjusts the humidity, it is, for example, a humidifier or a dehumidifier. The adjustment unit 51 may adjust at least one of the temperature and humidity for each type of first gas, or it may change at least one of the temperature and humidity at predetermined intervals during measurement of the same first gas.

[0141] The adjustment unit 51 adjusts at least one of the temperature and humidity of the first gas in the target sample receiving unit 50, thereby enabling the odor measuring device 100 to send the first gas to the sensor chamber 60 under conditions corresponding to, for example, the type of first gas (gas weight, volatility, etc.). Furthermore, according to this, the odor measuring device 100 can send a first gas of a stable concentration to the sensor chamber 60, thereby improving the accuracy of the measurement.

[0142] [Sensor Chamber 60] The sensor chamber 60 is a space for housing a sensor element 31 for measuring odor substances. The sensor chamber 60 is connected to the second port 502 of the target sample receiving section 50. Specifically, the sensor chamber 60 is equipped with a gas supply port 601 and a gas outlet 602, and the second port 502 of the target sample receiving section 50 is connected to the gas supply port 601.

[0143] The sensor chamber 60 includes a plurality of sensor elements 31A capable of outputting measurement results corresponding to odor substances contained in the first gas. Each of the plurality of sensor elements 31A may be a sensor element 31 having a different resin composition as its material receiving layer. That is, each of the plurality of sensor elements 31A may have different sensitivity and specificity to odor substances. The sensor chamber 60 in Figure 1 includes, as an example, a sensor element 31 and a sensor element 31b, but is not limited thereto. The sensor chamber 60 in Figure 1 also includes a sensor element 31c having a different resin composition as its material receiving layer than sensor elements 31 and 31b. Sensor elements 31 and 31b are capable of outputting measurement results corresponding to the same odor substance contained in the first gas, but the measurement results they output are different. The measurement results corresponding to the odor substance are, for example, measurement results corresponding to the concentration of the odor substance. In the following description, unless otherwise distinguished, sensor elements 31, 31b, 31c and sensor element 31d (described later) will be collectively referred to as "sensor element 31".

[0144] Sensor elements 31, each having a different resin composition as a material receiving layer, may be installed in any combination and arrangement within the sensor chamber 60. Furthermore, multiple sensor elements 31, each having the same resin composition as a material receiving layer, may be installed within the sensor chamber 60.

[0145] Here, sensor element 31 and sensor element 31b may each be sensor elements capable of outputting measurement results corresponding to different odor substances. For example, the sensor chamber 60 may be equipped with sensor element 31 capable of outputting measurement results corresponding to odor substances contained in the first gas, and sensor element 31b capable of outputting measurement results corresponding to a second odor substance different from the odor substances contained in the first gas. For example, the odor sensor 30 may be equipped with sensor elements 31 and 31b whose resin compositions used in the odor substance receiving layer 315 are different from each other.

[0146] By providing multiple sensor elements 31 using resin compositions with different odor-adsorbing properties in the odor-receiving layer 315, the odor measuring device 100 can simultaneously perform estimations for multiple odor substances. In addition to the sensor element 31 according to one embodiment of the present invention, a sensor element 31 that does not contain a surfactant (B) in the odor-receiving layer 315 may also be used in combination.

[0147] Furthermore, using the odor measuring device 100, it is possible to obtain a first change pattern showing the change in the electrical conductivity of the sensor element 31 and a second change pattern showing the change in the electrical conductivity of the sensor element 31b for each known odor substance. The estimation model 22 may be generated by machine learning using both the first and second change patterns. Since the odor measuring device 100 estimates the odor substance using the estimation model 22 thus generated, it is possible to identify each odor substance with greater precision.

[0148] The sensor chamber 60 in Figure 1, as an example, is equipped with multiple sensor elements 31A arranged in a 4x4 grid. The number of sensor elements 31A and the arrangement of the sensor elements 31A are not limited. The total number of sensor elements 31A in the sensor chamber 60 is also not particularly limited, but may be, for example, 2, 16, or 64.

[0149] The material of the inner surface of the sensor chamber 60 is preferably an inert material to odor substances, similar to the material of the sample receiving section 50. Examples of materials inert to odor substances include glass, metal, and resin. When metal is used, stainless steel (SUS) is preferred, and when resin is used, fluororesin, polypropylene (PP), polyethylene (PE), ABS resin, and polyethylene terephthalate (PET) are preferred. If the material of the inner surface of the sensor chamber 60 is a material that adsorbs odor substances contained in the first gas, the adsorption of odor substances on the sensor chamber may reduce the amount of change in the output from the sensor element 31 in subsequent measurements, which may prevent the odor measuring device 100 from performing accurate measurements.

[0150] [Multiple sensor elements 31A (sensor element group 31A)] Multiple sensor elements 31A may include thin films. For example, the odor substance receiving layer 315 in Figures 2 and 3 is a thin film.

[0151] One possible method for supplying the first gas containing odor substances into the sensor chamber 60 is to install a vacuum pump on the gas outlet 602 side of the sensor chamber 60 and use the vacuum pump to draw in the gas, thereby supplying the odor substances to the sensor chamber 60 from the gas supply port 601 side. However, if the sensor elements 31 and 31b are equipped with thin films, the thin films may expand if the inside of the sensor chamber 60 is under negative pressure, which could prevent the sensor elements 31 and 31b from outputting stable measurement results. In the odor measuring device 100 according to this embodiment, the gas supply unit 80 pushes the gas from the sensor chamber 60 and the first port 501 side of the target sample receiving unit 50, thereby supplying the first gas to the sensor chamber 60. As a result, the pressure inside the sensor chamber 60 is positive. Therefore, the odor measuring device 100 can obtain stable measurement results even if multiple sensor elements 31A are equipped with thin films.

[0152] Furthermore, the thin films of the multiple sensor elements 31A may also contain a conductive carbon material, a resin composition, and a surfactant.

[0153] [Gas supply unit 80] The gas supply unit 80 is connected to the first port 501 of the target sample receiving unit 50, and by sending the second gas into the target sample receiving unit 50, the first gas is sent from inside the target sample receiving unit 50 toward the sensor chamber 60.

[0154] A valve 81 may be provided between the gas supply unit 80 and the target sample receiving unit 50. The start and stop of gas supply from the gas supply unit 80 may be adjusted by opening and closing the valve 81.

[0155] In this way, the gas supply unit 80 pushes the gas from the first port 501 side of the target sample receiving unit 50, sending the first gas into the sensor chamber 60, so the pressure inside the sensor chamber 60 is positive. Therefore, the odor measuring device 100 can obtain stable measurement results. In addition, since the second gas can be supplied by opening and closing the valve 81, the odor measuring device 100 can send the first gas from the target sample receiving unit 50 to the sensor chamber 60 at any timing. As a result, when the odor measuring device 100 repeatedly measures odor substances contained in the first gas using the sensor element group 31A, the reproducibility of the waveform shape output by each sensor element 31 can be improved.

[0156] The second gas may be an inert gas or air. Examples of inert gases include argon and nitrogen. If the second gas is an inert gas, the gas supply unit 80 may be a gas cylinder.

[0157] Furthermore, if the second gas is air, the gas supply unit 80 may be a pump. In this case, In order to remove components that react with the first gas contained within the target sample receiving section 50, the odor measuring device 100 may, for example, be equipped with an activated carbon filter on the first opening 501 side of the target sample receiving section 50.

[0158] The odor measuring device 100 may further include a mass flow controller between the first port 501 side of the target sample receiving section 50, more specifically between the valve 81 and the gas supply section 80. The odor measuring device 100 employing this configuration can send the first gas from the target sample receiving section 50 to the sensor chamber 60 at a constant flow rate, and multiple sensor elements 31A can stably output.

[0159] In Figure 1, the first and second gases exiting from the sample receiving section 50 pass through the tube 93 and the sensor chamber 60, but the device is not limited to this configuration. Since the sample receiving section 50 of the odor measuring device 100 has a larger volume than the sensor chamber 60, it is not necessary to send the entire volume of the first gas inside the sample receiving section 50 to the sensor chamber 60 during measurement. Also, when purging the inside of the sample receiving section 50 with the second gas after measurement, it is not necessary for the sample receiving section 50 and the sensor chamber 60 to be connected. Therefore, the odor measuring device 100 may be configured such that a valve (not shown) is placed in the tube 93, allowing the first and second gases exiting from the sample receiving section 50 to be exhausted without passing through the sensor chamber 60.

[0160] First, the configuration of the odor measuring device 100 according to one embodiment of the present invention will be explained using Figure 1. Figure 1 is a block diagram showing an example of the configuration of the odor measuring device 100.

[0161] As shown in Figure 1, the odor measuring device 100 includes an estimation device 10 and an odor sensor 30.

[0162] [Estimation device 10] The estimation device 10 is a device that estimates odor substances detected by the odor sensor 30. The estimation device 10 is, for example, a computer and is equipped with a CPU and memory (not shown). The estimation device 10 is communicably connected to the odor sensor 30. Specifically, the estimation device 10 performs the estimation of odor substances by analyzing the measured values ​​obtained from the odor sensor 30. If the sensor chamber 60 further includes a sensor element 31c that uses a different resin composition for the substance receiving layer 315 than the sensor element 31 and sensor element 31b, the estimation device 10 may further acquire and analyze measured values ​​measured by a voltmeter by supplying a constant voltage to the sensor element 31c. The estimation device 10 may also display the measured values ​​themselves, waveforms plotted from the measured values, and the estimation results of unknown odor substances based on the estimation model. The estimation device 10 may also display numerical values ​​and graphs showing the change in the abundance ratio of each odor substance for a gas containing multiple odor substances. The estimation device 10 may also generate an estimation model 22 used to estimate odor substances.

[0163] <Generation of Estimated Model 22> Next, the configuration of the odor measuring device 100, which performs the process of generating an estimation model 22 used to estimate odor substances, and the process of generating the estimation model 22 will be explained with reference to Figures 5 and 6.

[0164] The estimation model 22 is generated by machine learning using training data that includes a combination of measured values ​​obtained by the voltmeter 33 when each of several odor substances is adsorbed onto at least one sensor element, and identification information specific to the odor substance to which the measured value was obtained. Here, the identification information specific to the odor substance may be, for example, the name of the odor substance, the CAS number, and the chemical formula.

[0165] (Configuration of estimation device 10 (generation of estimation model 22)) Figure 5 is a functional block diagram showing an example of the configuration of the odor measuring device 100. For the sake of clarity, components having the same function as those described in Figure 1 are denoted by the same reference numerals, and their descriptions are not repeated.

[0166] As shown in Figure 5, the estimation device 10 includes an input unit 15, a control unit 1, and a storage unit 2.

[0167] The input unit 15 is for receiving various input operations from the user, and may be, for example, a keyboard, mouse, touch panel, etc.

[0168] The control unit 1 comprises a measurement value acquisition unit 11 (acquisition unit), a change pattern analysis unit 12 (analysis unit), a learning control unit 13, and an estimation model generation unit 14.

[0169] The measurement value acquisition unit 11 acquires measurement values ​​from the voltmeter 33. The measurement value acquisition unit 11 also uses the acquired measurement values ​​to calculate values ​​indicating the electrical conductivity of the sensor element 31 (e.g., resistance and impedance). The measurement value acquisition unit 11 may acquire measurement values ​​from the voltmeter 33 at predetermined time intervals (e.g., 0.1-second intervals).

[0170] The change pattern analysis unit 12 analyzes the change in electrical conductivity of at least one sensor element 31 over time. The change pattern analysis unit 12 uses the resistance value calculated by the measurement value acquisition unit 11 to calculate a value indicating the amount of change in the electrical conductivity of the sensor element 31 due to the adsorption of odor substances. The change pattern analysis unit 12 generates data showing a change pattern that indicates the time change of the calculated amount of change in electrical conductivity. If the generated change pattern is that of a known odor substance, the change pattern analysis unit 12 may associate the generated change pattern with identification information specific to the known odor substance and store it in the change pattern database 21 (training data).

[0171] The learning control unit 13 reads the change pattern database 21 from the memory unit 2 and controls the generation of an estimation model 22 using machine learning. Here, the change pattern database 21 is a database that includes combinations of measured values ​​obtained when multiple odor substances are adsorbed onto the sensor element 31 and identification information unique to the known odor substances to which the measured values ​​were given. The learning control unit 13 inputs the change patterns read from the change pattern database 21 to the estimation model generation unit 14. The learning control unit 13 also compares the identification information of the odor substances corresponding to the change patterns input to the estimation model generation unit 14 with the estimation results output from the estimation model generation unit 14, and outputs a correction instruction to the estimation model generation unit 14 according to the comparison result.

[0172] The estimation model generation unit 14 generates an estimation model 22 using a machine learning algorithm that utilizes the change patterns stored in the change pattern database 21. The estimation model generation unit 14 may also be configured to generate the estimation model 22 using a known supervised machine learning algorithm. Examples of machine learning algorithms applicable to the estimation model generation unit 14 include the k-nearest neighbor method, logistic regression, support vector machines, random forests, and neural networks.

[0173] (Process to generate estimated model 22) The specific processing performed by each part of the control unit 1 will be explained below with reference to Figure 6. Figure 6 is a flowchart showing an example of the processing flow in which the estimation device 10 generates the estimation model 22. The estimation model 22 is generated by machine learning using training data that includes a combination of measured values ​​measured by the voltmeter 33 when each of a plurality of odor substances is adsorbed onto at least one sensor element 31, and identification information unique to the odor substance to which the measured value was given. Here, the identification information unique to the odor substance may be, for example, the name of the odor substance, the CAS number, and the chemical formula.

[0174] First, the measurement value acquisition unit 11 acquires the voltage value V0 measured by the odor sensor 30 before introducing the odor substance into the target sample receiving unit 50, and calculates the resistance value R0. The resistance value R0 is preferably 200 to 1000 Ω, more preferably 250 to 900 Ω, and most preferably 300 to 800 Ω. Then, the odor substance is placed into the target sample receiving unit 50 (step S1).

[0175] Meanwhile, the input unit 15 receives input such as the name of a known odor substance introduced into the target sample receiving unit 50 (step S2). The processing in step S2 may be performed before step S1.

[0176] Next, the measurement value acquisition unit 11 acquires data (waveform or time-dependent change pattern) of the change in voltage value V (ΔV) before and after the process of adsorption and desorption of odor substances to the sensor element 31 (step S3).

[0177] Next, the change pattern analysis unit 12 associates the change in voltage value V (ΔV) data (waveform or time-dependent change pattern) during the processes before and after adsorption and desorption of odor substances with the names of known odor substances that have been input and stores them in the change pattern database (step S4).

[0178] If no change patterns are stored for a given type of existing odor substance (NO in step S5), that is, if there is still insufficient data to use for machine learning, the process returns to step S1.

[0179] If change patterns for a predetermined type of existing odor substance are stored (YES in step S5), the learning control unit 13 reads the change patterns for known odor substances stored in the change pattern database 21 and inputs them to the estimation model generation unit 14. The estimation model generation unit 14 generates an estimation model 22 by machine learning based on the time-series change patterns (or features extracted from the change patterns) stored in the change pattern database 21 (step S6).

[0180] The estimation model generation unit 14 stores the estimation model 22 generated by predetermined machine learning in the storage unit 2 (step S7).

[0181] In the examples shown in Figures 5 and 6, the estimation device 10 generates the estimation model 22, but this is not limited to this. For example, an external computer different from the estimation device 10, which has the same functions as the learning control unit 13 and the estimation model generation unit 14, may be provided with the same data as the change pattern database 21 to create the estimation model 22.

[0182] <Estimation of odor molecules> Next, the configuration of the odor measuring device 100a, which estimates odor substances using the estimation model 22, and the estimation process will be explained with reference to Figures 7 and 8.

[0183] (Configuration of estimation device 10a (Execution of estimation process)) Figure 7 is a functional block diagram showing an example of the configuration of the odor measuring device 100a. For the sake of clarity, components having the same function as those described in Figures 1 and 5 are denoted by the same reference numerals, and their descriptions are not repeated.

[0184] As shown in Figure 7, the estimation device 10a comprises a control unit 1a, a storage unit 2a, and an output unit 18. Here, Figure 7 shows an example configuration when the estimation device 10 shown in Figure 5 is used for odor substance estimation processing. In other words, the estimation device 10 shown in Figure 5 and the estimation device 10a shown in Figure 7 may be computers with the same hardware configuration.

[0185] The output unit 18 is for presenting the estimation results to the user and may be, for example, a display, speaker, lamp, etc.

[0186] The control unit 1a includes a measurement value acquisition unit 11 (acquisition unit), a change pattern analysis unit 12 (analysis unit), an estimation unit 16, and an output control unit 17.

[0187] The estimation unit 16 uses the estimation model 22 to estimate odor substances from the analysis results obtained by analyzing the measured values ​​acquired from the odor sensor 30.

[0188] The output control unit 17 controls the output unit 18 to output the estimation result.

[0189] (Estimation process) The specific processes performed by each part of the control unit 1a will be explained below using Figure 8. Figure 8 is a flowchart showing an example of the process flow in which the estimation device 10a estimates odor substances.

[0190] First, the measurement value acquisition unit 11 acquires the voltage value V0 measured by the odor sensor 30 before introducing the odor substance into the target sample receiving unit 50, and calculates the resistance value R0. Then, an unknown odor substance (regardless of its properties) is introduced into the target sample receiving unit 50 (step S11).

[0191] Next, the measurement value acquisition unit 11 acquires data (waveform or time-dependent change pattern) of the change in voltage value V (ΔV) before and after the adsorption and desorption of the unknown (i.e., the odor substance to be estimated) onto the sensor element 31 (step S12).

[0192] Next, the estimation unit 16 estimates unknown odor substances based on the estimation model 22, using the time-dependent change pattern (or features extracted from the change pattern) (step S13).

[0193] The output control unit 17 controls the output unit to output the estimation result (step S14).

[0194] In the embodiments described above, an estimation device 10 that generates an estimation model 22 and an estimation device 10a that estimates odor substances using the estimation model 22 were described. Note that the estimation device 10 and the estimation device 10a may be separate devices or may be a single device.

[0195] <Manufacturing method for sensor elements> The following describes a manufacturing method for producing multiple types of sensor elements 31 used in the odor measuring device 100. The odor substance receiving layer 315 of the sensor element 31 can use slurries with various compositions as its raw material.

[0196] (Slurry preparation process) First, several types of slurries with different mixing ratios of conductive carbon material and resin composition are prepared. The mixing ratio of the conductive carbon material and resin composition can be appropriately set according to the desired sensitivity and detection specificity of the odor substance receiving layer 315. In addition to the conductive carbon material and resin composition, the slurry may also contain solvents, additives, and surfactants.

[0197] (Electrode placement process) Next, electrodes are placed on the substrate. The electrodes may comprise a first electrode and a second electrode. The first and second electrodes may be arranged in parallel lines, parallel curves, a comb shape, and concentric circles. Furthermore, in any of the shapes described above, it is preferable that the first and second electrodes are arranged symmetrically with respect to a line or point. Moreover, it is even more preferable that the first and second electrodes are arranged in parallel lines or parallel curves. The first and second electrodes are composed of two metal wires (313a and metal wire 313c) arranged in a T-shape so that the first metal wire 313C is perpendicular to each other, and the second metal wire 313D is composed of two metal wires (313c and metal wire 313d) arranged in a T-shape so that they are perpendicular to each other, and it is preferable that the first metal wire 313C and the second metal wire 313D are arranged in parallel lines so that metal wire 313a and metal wire 313c face each other. With the first and second metal wirings arranged in this manner, the odor measuring device 100 can measure odor substances contained in the gas with high accuracy.

[0198] (Area definition process) Next, coating areas are defined on the substrate on which the electrodes are placed, for applying each of several types of slurries. The coating areas may be defined, for example, by the placement of a resist. Also, if the slurry is dispensed from a nozzle during the coating process, the coating areas may be defined according to the nozzle diameter. The resist M is placed to define the coating area 330. The substrate 311 is exposed in the coating area 330.

[0199] The area of ​​the coating region 330 may be specified to be the same for each of the multiple types of slurries. That is, even if the slurries have different mixing ratios of conductive carbon material and resin composition, the area of ​​the coating region 330 for applying the slurry may be uniform. This reduces the variation in the area of ​​the multiple types of odor substance receiving layers 315 after drying, even when using multiple types of slurries with different mixing ratios.

[0200] The coated area 330 is, for example, circular, but its shape is not limited to this. The coated area 330 may be circular or strip-shaped. This forms a circular or strip-shaped odor substance receiving layer 315.

[0201] If the coated area 330 is circular, the diameter of the circle may be 0.2 mm or more and 5 mm or less. If the coated area 330 is strip-shaped, the length of the strip in the short direction may be 0.2 mm or more and 5 mm or less. This results in the formation of a circular odor substance receiving layer 315c with a diameter of 0.2 mm or more and 5 mm or less, and a circular odor substance receiving layer 315d with a length of the strip in the short direction of 0.2 mm or more and 5 mm or less.

[0202] The method for applying resist M is not particularly limited, but examples include silk-screen printing of solder resist onto a defined area and then UV curing of the solder resist, attaching a resist film to a substrate, and curing only the resist in a defined area and removing the uncured portion.

[0203] (Coating process) Next, each of the multiple types of slurry is applied to the coating area 330. Conventional methods can be applied to the slurry, and it may be dispensed by dropping from a nozzle, spraying, or spin coating. The method of applying the slurry by dropping from a nozzle is particularly preferred, and for example, by using a SUS metal needle nozzle (inner diameter 0.1 mmΦ, outer diameter 0.23 mm) with the IMAGE MASTER350PCSmart manufactured by Musashi Engineering Co., Ltd., the desired coating shape can be obtained.

[0204] (drying process) Finally, the slurry applied to the coating area 330 is dried to form the odor substance receiving layer 315. The method for drying the slurry is not particularly limited, but for example, a method can be employed in which the slurry is heated at 100°C for 1 hour at atmospheric pressure, and then heated at 100°C for 1 hour under reduced pressure in a vacuum dryer.

[0205] <Examples of implementation using software> The control blocks (especially the control unit 1) of the estimation devices 10 and 10a may be implemented by logic circuits (hardware) formed on an integrated circuit (IC chip) or by software.

[0206] In the latter case, the estimation devices 10 and 10a are equipped with a computer that executes instructions for a program, which is software that realizes each function. This computer is equipped with, for example, one or more processors and a computer-readable recording medium that stores the program. The object of the present invention is achieved when the processor reads the program from the recording medium and executes it in the computer. For example, a CPU (Central Processing Unit) can be used as the processor. As the recording medium, a "tangible medium that is not temporary," such as ROM (Read Only Memory), can be used, as well as tape, disk, card, semiconductor memory, programmable logic circuit, etc. It may also be further equipped with RAM (Random Access Memory) for expanding the program. Furthermore, the program may be supplied to the computer via any transmission medium capable of transmitting the program (such as a communication network or broadcast wave). In one aspect of the present invention, the program can also be realized in the form of a data signal embedded in a carrier wave, which is embodied by electronic transmission.

[0207] [Summary] <1> A resin composition according to one embodiment of the present invention is a resin composition for forming an odor substance receiving layer, and comprises a polyurethane resin (A), a surfactant (B), and a conductive carbon material (C). <2> The aforementioned <1> The resin composition described above may have a surfactant (B) with an HLB value of 8 to 18. <3> The aforementioned <1> or <2> The resin composition described herein may have a weight ratio [(A) / (B)] of 1.0 to 4.0 between the polyurethane resin (A) and the surfactant (B). <4> The aforementioned <1> ~ <3> The resin composition described in any of the above may contain the conductive carbon material (C) in an amount of 5 to 75% by weight relative to 100% by weight of the total of the polyurethane resin (A), the surfactant (B), and the conductive carbon material (C). <5> The sensor element according to one embodiment of the present invention is the aforementioned <1> ~ <4> A sensor element comprising an odor substance receiving layer containing the resin composition described in any of the above, a first metal wiring, and a second metal wiring, wherein the first metal wiring and the second metal wiring are spaced apart, and the odor substance receiving layer is in contact with at least a portion of the first metal wiring and at least a portion of the second metal wiring. <6> The odor sensor according to one embodiment of the present invention is the aforementioned <5> The odor sensor comprises at least one sensor element as described above, a power supply for supplying power to the sensor element, and a measuring instrument that outputs a measurement value indicating the electrical conductivity of the odor substance receiving layer of the sensor element powered by the power supply. <7> The aforementioned <6> In the odor sensor described above, the power supply may supply a constant current or apply a constant voltage to the at least one sensor element. <8> The odor measuring device according to one embodiment of the present invention is the <6> or <7> An odor measuring device comprising the odor sensor and estimation device described in [reference], wherein the estimation device comprises an acquisition unit that acquires the measured value from the measuring instrument, an analysis unit that analyzes the change in electrical conductivity of at least one sensor element over time, and an estimation unit that estimates odor substances based on an estimation model, the estimation model being generated by machine learning using training data that includes a combination of measured values ​​measured by the measuring instrument when each of a plurality of odor substances is adsorbed onto at least one sensor element, and identification information specific to the odor substance to which the measured value was given. <9> The control program according to one embodiment of the present invention is the <8> A control program for causing a computer to function as the odor measuring device described above, wherein the computer functions as the acquisition unit, the analysis unit, and the estimation unit.

[0208] [5. Embodiments of Odor Sensor and Water Quality Evaluation Device for Water Quality Assessment] The following describes embodiments in which the odor sensor element, odor sensor, and odor measuring device described above are used as an odor sensor element for water quality evaluation, an odor sensor for water quality evaluation, and a water quality evaluation device.

[0209] In this embodiment, the water quality assessment is intended to target wastewater from factories, water stored in dams, and raw water for water treatment taken by water treatment plants. However, it is not limited to these, and applies to various types of water that may emit odors due to the presence of impurities such as harmful substances, microorganisms, and sludge. For example, wastewater from chemical plants, pulp mills, starch mills, dye mills, and sewage treatment plants, as well as wastewater from restaurants, can also be subject to water quality assessment in this embodiment.

[0210] The evaluation results from water quality assessment can include various things besides distinguishing between smelly and odorless water (for examples of these evaluation results, see the explanation of "identification information" below).

[0211] In this embodiment, the above-described embodiment is applied, and n odor sensor elements are used, each functioning as an odor sensor element for water quality evaluation. The number n of these water quality evaluation odor sensor elements is preferably two or more for applications such as substituting for the sensory evaluation of odors perceived by humans, but may be one for applications such as detecting a single type of odor substance. Furthermore, the number n of water quality evaluation odor sensor elements may be 256 or less, preferably 128 or less, and more preferably 64, from the viewpoint of cost and device size. The number n of water quality evaluation odor sensor elements may be one or two. In these n water quality evaluation odor sensor elements, it is preferable that the resin composition in the odor substance receiving layer 315, particularly the type of surfactant, is different from one another.

[0212] Furthermore, the odor substance receiving layer 315 can also be described as the "sensitive membrane" of the odor sensor element for water quality evaluation. Additionally, the odor sensor element for water quality evaluation can be said to have the function of a probe in the water quality evaluation odor sensor.

[0213] In a water quality evaluation device using n odor sensor elements for water quality evaluation, the change patterns showing the change in electrical conductivity of each odor sensor element can be used as the 1st to nth change patterns to generate the estimation model 22.

[0214] To generate the estimation model 22, machine learning can be performed using training data that includes a combination of a set of 1st to nth change patterns and identification information indicating the evaluation result for the sample gas, for a sample gas that has already been evaluated by some other method.

[0215] This identification information should be set according to the evaluation purpose of the water quality evaluation device. Examples of this identification information include the following: (1) Information to distinguish between smelly and not smelly. (2) Quantitative information indicating the degree of odor. (3) Information that identifies the proportion of each of the multiple odorants contained in the sample gas. The combination of odorants can be selected from groups such as thiols, aldehydes, higher fatty acids, ammonia, hydrogen sulfide, methyl captan, methyl sulfide, and methyl disulfide. Note that there may be only one type of odorant. Even if there are multiple types, the information may indicate whether or not each odorant is present in a certain amount, without specifying their proportions.

[0216] Furthermore, the identification information may be a combination of multiple types of information. For example, if (1) and (3) above are combined, the water quality evaluation device will be able to output evaluation results that include not only subjective information such as "smelly" or "not smelly," but also information that identifies the composition ratio of each target odor substance, such as "The composition ratio of thiols, aldehydes, higher fatty acids, ammonia, hydrogen sulfide, methyl captan, methyl sulfide, and methyl disulfide is A:B:C:D:E:F:G:H."

[0217] As described above, the odor sensor element for water quality evaluation of this embodiment comprises a first metal wiring, a second metal wiring spaced apart from the first metal wiring, and an odor substance receiving layer that is in contact with at least a portion of the first metal wiring and at least a portion of the second metal wiring and contains a resin composition comprising a polyurethane resin (A), a surfactant (B), and a conductive carbon material (C).

[0218] Furthermore, the odor sensor for water quality evaluation of this embodiment is a water quality evaluation odor sensor comprising at least one odor sensor element for water quality evaluation, a power supply for supplying power to the odor sensor element for water quality evaluation, and a measuring instrument that outputs a measurement value indicating the electrical conductivity of the odor substance receiving layer of the odor sensor element supplied with power from the power supply.

[0219] Furthermore, the water quality evaluation device of this embodiment is a water quality evaluation device comprising the water quality evaluation odor sensor and an estimation device, wherein the estimation device comprises an acquisition unit that acquires the measured values ​​from the measuring instrument, an analysis unit that analyzes the change in electrical conductivity of the at least one water quality evaluation odor sensor element over time, and an estimation unit that estimates the evaluation of a target gas emitted from the water to be evaluated based on an estimation model, wherein the estimation model is generated by machine learning using training data that includes a combination of analysis results obtained for each of a plurality of types of target gases, obtained by the analysis unit when the target gas is brought into contact with the at least one water quality evaluation odor sensor element, and identification information of the target gas.

[0220] Furthermore, the control program of this embodiment is a control program for causing a computer to function as the water quality evaluation device, and is a control program for causing the computer to function as the acquisition unit, the analysis unit, and the estimation unit.

[0221] Odor sensor elements for water quality evaluation, odor sensors for water quality evaluation, and water quality evaluation devices can also be realized by using various known odor sensor elements other than the odor sensor elements for water quality evaluation described above.

[0222] However, by using the odor sensor element for water quality evaluation described above, that is, an odor-receiving layer containing an odor-receiving layer containing a resin composition including polyurethane resin (A), surfactant (B), and conductive carbon material (C), if the number and type of odor sensor elements for water quality evaluation (type of resin composition in the odor-receiving layer 315) are appropriately selected, even with the same hardware configuration, it is possible to achieve measurements that show more appropriate sensitivity to the target gas emitted from the water under evaluation, depending on the training data used for machine learning. The above odor-receiving layer is suitable for sensing the amount of a specific odor substance or the ratio of multiple odor substances from among volatile organic compounds (VOCs) containing impurities, which is advantageous for the analysis of the target gas emitted from the water under evaluation.

[0223] Furthermore, the aforementioned water quality evaluation device can perform comprehensive evaluations of target gases emitted from various types of water samples, depending on the training data used for machine learning, and the estimation model can be updated based on these evaluations.

[0224] The technologies disclosed in Patent Documents 4 to 6, listed in the Prior Art section, use conventional odor sensors, which often leads to discrepancies between their measurement results and, for example, how humans perceive odors. Humans perceive more than one type of odor substance as offensive, and it is crucial to accurately sense the odor substance causing the offensive odor from among the impurities. However, the technologies disclosed in Patent Documents 4 to 6 were insufficient in this regard.

[0225] The present invention is not limited to the embodiments described above, and various modifications are possible within the scope of the claims. Embodiments obtained by appropriately combining the technical means disclosed in different embodiments are also included in the technical scope of the present invention.

[0226] 〔summary〕 An odor sensor element for water quality evaluation according to embodiment 1 of the present invention comprises a first metal wiring, a second metal wiring spaced apart from the first metal wiring, and an odor substance receiving layer in contact with at least a portion of the first metal wiring and at least a portion of the second metal wiring, and containing a resin composition comprising a polyurethane resin (A), a surfactant (B), and a conductive carbon material (C).

[0227] In the odor sensor element for water quality evaluation according to embodiment 2 of the present invention, the surfactant (B) may have an HLB value of 8 to 18 in embodiment 1.

[0228] In the odor sensor element for water quality evaluation according to embodiment 3 of the present invention, the weight ratio of the polyurethane resin (A) to the surfactant (B) [(A) / (B)] may be 1.0 to 4.0 in embodiment 1 or 2 above.

[0229] In any of the above embodiments 1 to 3, the odor sensor element for water quality evaluation according to embodiment 4 of the present invention may contain 5 to 75% by weight of the conductive carbon material (C) relative to 100% by weight of the total of the polyurethane resin (A), the surfactant (B), and the conductive carbon material (C).

[0230] In the odor sensor element for water quality evaluation according to embodiment 5 of the present invention, in any of embodiments 1 to 4 above, the polyurethane resin (A) may contain an aromatic polyisocyanate.

[0231] A water quality evaluation odor sensor according to embodiment 6 of the present invention comprises at least one water quality evaluation odor sensor element described in any of embodiments 1 to 5 above, a power supply for supplying power to the water quality evaluation odor sensor element, and a measuring instrument that outputs a measurement value indicating the electrical conductivity of the odor substance receiving layer of the water quality evaluation odor sensor element supplied with power from the power supply.

[0232] In the odor sensor for water quality evaluation according to embodiment 7 of the present invention, in embodiment 6, the power supply may supply a constant current or apply a constant voltage to the at least one odor sensor element for water quality evaluation.

[0233] A water quality evaluation device according to aspect 8 of the present invention is a water quality evaluation device comprising a water quality evaluation odor sensor and an estimation device as described in aspect 6 or 7, wherein the estimation device comprises an acquisition unit that acquires the measured value from the measuring instrument, an analysis unit that analyzes the change in electrical conductivity of the at least one water quality evaluation odor sensor element over time, and an estimation unit that estimates the evaluation result for a target gas emitted from the water to be evaluated based on an estimation model, wherein the estimation model is generated by machine learning using training data that includes a combination of analysis results obtained for each of a plurality of types of target gases, obtained by the analysis unit when the target gas is brought into contact with the at least one water quality evaluation odor sensor element, and identification information of the target gas.

[0234] The control program according to aspect 9 of the present invention is a control program for causing a computer to function as a water quality evaluation device as described in aspect 8, and is a control program for causing the computer to function as the acquisition unit, the analysis unit, and the estimation unit. [Examples]

[0235] The present invention will be further described below with reference to examples and comparative examples, but the present invention is not limited thereto. Unless otherwise specified, % refers to weight percent and parts refers to parts by weight.

[0236] [Manufacturing Examples 1-11] <Preparation of polyester diol (x2)> A reaction vessel equipped with a stirring blade, a stirring device, a nitrogen inlet and outlet was fitted with a heating and cooling device, a thermometer, a temperature control device, a polymerization catalyst introduction tube, and a nitrogen introduction tube. This reaction vessel had a sealing structure that allowed for reduced pressure inside the vessel. Diols and dicarboxylic acids were added to the reaction vessel in the amounts listed in Table 1, and 0.5 parts by weight of titanium diisopropoxybistriethanolamine was added as a polymerization catalyst. The reaction vessel was then heated to 200°C while stirring, and the diol and dicarboxylic acid were reacted over 5 hours while flowing a nitrogen stream and distilling off the by-product water. Subsequently, the pressure inside the reaction vessel was reduced to 10 mmHg, and the reaction was allowed to proceed for another hour to obtain polyester diols (x2-1) to (x2-11).

[0237] The number-average molecular weights of the obtained polyester diols (x2) were measured by gel permeation chromatography (GPC) under the following conditions, and the results are shown in Table 1.

[0238] Device: HLC-8120 manufactured by Tosoh Corporation Column: TSK GEL GMH6 (2 pieces) [Manufactured by Tosoh Corporation] Measurement temperature: 40℃ Sample solution: 0.25% by weight THF (tetrahydrofuran) solution Solution injection volume: 100μl Detection device: Refractive index detector Furthermore, the number-average molecular weight was measured by dissolving polyester diol (x2) in THF, filtering out the undissolved portion through a glass filter, and using the resulting sample solution.

[0239] [Table 1]

[0240] [Manufacturing Examples 12-28] <Preparation of polyurethane resin (A)> Using the polyol (x) and polyisocyanate (y) listed in Table 2, polyurethane resin (A) was obtained by the method shown below.

[0241] Specifically, a reaction vessel equipped with a stirring blade, a stirring device, a nitrogen inlet and outlet was fitted with a heating and cooling device, a thermometer, a temperature control device, a polymerization catalyst introduction tube, and a nitrogen introduction tube. This reaction vessel had a sealing structure that allowed for reduced pressure inside the vessel. In the reaction vessel, polyol (x) containing polyoxyalkylenediol (x1) and / or polyester diol (x2) and polyisocyanate (y) were added in the amounts listed in Table 2 by weight. Dibutyltin dilaurate was then added as a reaction solvent and reaction catalyst. Subsequently, the inside of the reaction vessel was set to atmospheric pressure and a nitrogen atmosphere, the temperature inside the reaction vessel was raised to 65°C, and the inside of the reaction vessel was stirred for 10 hours while maintaining this temperature to react the polyol (x) and the polyisocyanate (y). After stirring, 5 parts of 1-butanol were added to the inside of the reaction vessel as a reaction stopper, and stirring inside the reaction vessel was continued for another hour. As a result, polyurethane resins (A-1) to (A-17) were obtained. Dimethylformamide (DMF) was used as the reaction solvent.

[0242] The number-average molecular weights of each obtained polyurethane resin (A) were measured by gel permeation chromatography (GPC) under the following conditions, and the results are shown in Table 3.

[0243] Device: HLC-8120 manufactured by Tosoh Corporation Column: One TSK GEL SuperH3000 (manufactured by Tosoh Corporation) and one TSK GEL SuperH4000 (manufactured by Tosoh Corporation) connected together. Measurement temperature: 40℃ Sample solution: 0.25 wt% DMF (dimethylformamide) solution Solution injection volume: 100μl Detection device: Refractive index detector Furthermore, the number-average molecular weight was measured by dissolving polyurethane resin (A) in DMF and filtering out the undissolved components using a glass filter to obtain the sample solution.

[0244] [Table 2]

[0245] [Table 3]

[0246] [Manufacturing Examples 29-41] <Preparation of higher alcohol ethylene oxide adducts> A reaction vessel equipped with a stirring blade, stirring device, nitrogen inlet, outlet, and ethylene oxide inlet, all having a sealing structure that allows for depressurization or pressurization of the inside of the reaction vessel, was fitted with a heating / cooling device, thermometer, pressure gauge, temperature control device, and nitrogen introduction tube. In the reaction vessel, under a nitrogen atmosphere, parts by weight of higher alcohols listed in Table 4, dried in 30 parts molecular sieves 3A for 2 hours, and 3 parts of potassium hydroxide as a catalyst were charged, and the vessel was purged with reduced pressure and nitrogen. The temperature inside the reaction vessel was raised to 160°C, and parts by weight of ethylene oxide listed in Table 4 were added dropwise while adjusting the flow rate so that the pressure inside the reaction vessel was 0.5 MPa (G), and the reaction was allowed to proceed. After the dropwise addition was completed, stirring was continued for 1 hour, and then the temperature inside the reaction vessel was lowered to room temperature to obtain higher alcohol ethylene oxide adducts (NS-1) to (NS-13).

[0247] [Table 4]

[0248] [Examples 1-236, Comparative Examples 1-17] <Slurry preparation> Polyurethane resin (A), surfactant (B), conductive carbon material (C), and ethyl acetate as a solvent (D) were weighed into polypropylene containers in the amounts listed in Tables 5 to 20 to obtain a mixture. This mixture was stirred at 2000 revolutions per minute for 60 minutes using a rotation / revolution mixer (ARE-310, manufactured by Thinky Co., Ltd.) to obtain a slurry. This slurry was used as a resin composition for forming the odor substance receiving layer. In Tables 5 to 20 below, "(A) / (B) ratio" refers to the weight ratio of polyurethane resin (A) to surfactant (B).

[0249] For the surfactants (B) other than the higher alcohol ethylene oxide adducts listed in Tables 5-20, commercially available products from Tokyo Chemical Industry Co., Ltd. were used. For the higher alcohol ethylene oxide adducts, (NS-1) to (NS-13) prepared by the method described above were used.

[0250] The conductive carbon materials (C) listed in Tables 5-20 were as follows: SUPER-C65 (carbon black) manufactured by MTI Corporation, VGCF-H (carbon nanotube) manufactured by Showa Denko Corporation, Denka Black (carbon black) manufactured by Denka Corporation, and Ketjenblack EC-300J (carbon black) and Ketjenblack EC-600JD (carbon black) manufactured by Lion Specialty Chemicals Ltd.

[0251] <Fabrication of sensor elements> A seal substrate (ICB-073, manufactured by Sunhayato Co., Ltd.) with multiple metal wirings having a gap width of 500 μm was cut out, and a seal substrate containing a pair of metal wirings was cut from it. The cut seal substrate was then further cut so that the length of the metal wiring was 3.5 cm.

[0252] The cut seal substrate was attached onto a glass plate with double-sided tape such that the metal wiring faced upward. Further, a vinyl tape was applied to mask the excess portion of the metal wiring such that the length of the exposed portion of the metal wiring was 3.0 cm. Subsequently, each of the slurries prepared by the aforementioned method was applied onto the exposed portion of the metal wiring using a bar coater (No. 4). After application, the coating was dried for 3 hours in a forced-air dryer heated to 100°C. After drying, the product was cooled to room temperature, then the metal wiring provided with the odorant-receiving layer was peeled off from the glass plate, whereby sensor elements (E-1) to (E-236) and comparative sensor elements (E'-1) to (E'-17) were obtained.

[0253]

Table 5

[0254]

Table 6

[0255]

Table 7

[0256]

Table 8

[0257]

Table 9

[0258]

Table 10

[0259]

Table 11

[0260]

Table 12

[0261] Table 13

[0262] Table 14

[0263] Table 15

[0264] Table 16

[0265] Table 17

[0266] Table 18

[0267] Table 19

[0268] Table 20

[0269] Examples 237 to 462, Comparative Examples 18 to 34 <Evaluation of Resin Composition and Sensor Element> The resin composition can be evaluated by comparing data obtained from the sensor element (E) and the comparative sensor element (E').

[0270] <Measurement method> A housing was fabricated that included an inlet for introducing the sample (odor substance) and a fan to create airflow so that the sample would spread evenly. Of the sensor elements (E-1) to (E-226) and comparison sensor elements (E'-1) to (E'-17) with lead wires soldered to bring terminals to the outside, the sensor element to be evaluated was installed inside the housing.

[0271] A 1mA constant current power supply and a voltmeter were attached to the ends of the lead wires that were brought out to the outside of the enclosure, and the voltage across both terminals of the lead wires was measured. The voltmeter readings were recorded on a computer.

[0272] The sample was immersed in filter paper so that the concentration of the sample inside the enclosure reached 200 ppm, and the filter paper was inserted through the inlet. Measurement began immediately after inserting the filter paper. 60 seconds after the start of measurement, the fan was rotated again for 60 seconds to expel steam from inside the enclosure while the measurement was performed. Voltage measurements were taken at 0.1-second intervals. The measurement was repeated 100 times under the same conditions.

[0273] The samples used were hexane, ethyl acetate, methanol, diethyl carbonate, or toluene.

[0274] <Evaluation Method> The electrical resistance R was calculated using Ohm's law, based on the voltage measured at each time point and the current value of 1 mA supplied from the constant current power supply. The resistance R0 before sample introduction was measured in advance, and R / R0 was calculated.

[0275] The responsiveness of the sensor element to each sample was analyzed using the k-nearest neighbor method, based on the time variation of R / R0 at 0.1-second intervals. The above measurements were performed on sensor elements (E-1) to (E-226) or comparative sensor elements (E'-1) to (E'-17). A total of 500 measurement data points (100 times x 5 samples) corresponding to each example and comparative example were randomly divided into training data:test data = 80:20, and a classifier (learning model) was created using the k-nearest neighbor method on the training data. The accuracy rate when classifying the test data for each example and comparative example was used as an indicator of the sensor element's performance, with a higher accuracy rate indicating higher performance as a sensor element. In creating the classifier and calculating the accuracy rate for each example, both data obtained from the corresponding sensor element (E) and data obtained from a comparative sensor element (E') using the same polyurethane resin (A) as the sensor element (E) were used.

[0276] <Evaluation Results> The evaluation results are shown below.

[0277] [Table 21]

[0278] [Table 22]

[0279] [Table 23]

[0280] [Table 24]

[0281] [Table 25]

[0282] [Table 26]

[0283] The accuracy rates calculated in the performance evaluation described above will be compared between odor sensors using the sensor elements manufactured in Examples 1 to 226 and odor sensors using the sensor elements manufactured in Comparative Examples 1 to 17.

[0284] For example, the accuracy rate of the odor sensor in Example 237, which used sensor element (E-1), was 72%, while the accuracy rate of the odor sensor in Comparative Example 26, which used a comparative sensor element (E'-9) that used the same polyurethane resin (A) as sensor element (E-1), was 27%.

[0285] As shown in Tables 21-26, the accuracy of the odor sensors in Examples 237-462, which used sensor elements (E-1)-(E-226), was higher than that of the odor sensors in Comparative Examples 18-34, which used comparative sensor elements (E'-1)-(E'-17).

[0286] A resin composition according to one embodiment of the present invention and an odor sensor using a sensor element made therefrom can be said to have good odor identification performance.

[0287] Furthermore, the Rmax / R0 value tended to decrease as the conductive carbon material (C) content increased. Since a smaller Rmax / R0 value increases measurement error, a larger Rmax / R0 value is desirable.

[0288] [Examples 463-472] <Evaluation of the content of conductive carbon material (C)> The R / R0 value immediately after the start of measurement can be controlled by changing the content of conductive carbon material (C). R / R0 was measured using each sensor element (E-227) to (E-236) in the same manner as described above. After the measurement was completed, the R / R0 value at 1 second after the start of measurement was extracted and recorded in Table 27. In addition, the maximum value of R during measurement was defined as Rmax, and the Rmax / R0 (%) value is also recorded in Table 27.

[0289] [Table 27]

[0290] As shown in Table 27, the R / R0 value at 1 second after the start of measurement increases as the conductive carbon material (C) content increases, specifically when it is 25% by weight or more, and the R / R0 value at 1 second after the start of measurement increases particularly significantly when the conductive carbon material (C) content is in the range of 30% by weight or more. Since a larger R / R0 at 1 second after the start of measurement leads to a reduction in measurement time and power consumption, it can be said that the conductive carbon material (C) content is preferably 25% by weight or more, and particularly preferably 30% by weight or more. Furthermore, when the conductive carbon material (C) content is 75% by weight or less, the adhesion of the conductive carbon material (C) to the seal substrate is better, and it is more suitable for the sensor element (E).

[0291] On the other hand, as shown in Table 27, the Rmax / R0 value decreases as the content of conductive carbon material (C) increases, and the measurement error increases. However, in Examples 463 to 472, in the range where the content of conductive carbon material (C) is 75% by weight or less, the Rmax / R0 value does not decrease significantly, and it is considered that the measurement error is kept small. Therefore, from the viewpoint of keeping the measurement time short and keeping the measurement error small to obtain a good accuracy rate, the content of conductive carbon material (C) is preferably 25 to 75% by weight, more preferably 30 to 65% by weight, and most preferably 35 to 55% by weight, relative to 100% by weight of the total of polyurethane resin (A), surfactant (B), and conductive carbon material (C). Alternatively, from the viewpoint of sensitivity to receiving odor substances, the content of the conductive carbon material (C) may be 5 to 30% by weight, 5 to 20% by weight, or 5 to 10% by weight, based on 100% by weight of the total of the polyurethane resin (A), surfactant (B), and conductive carbon material (C).

[0292] [Example 473, Comparative Example 35] <Evaluation of odor sensors and odor measuring devices> The odor sensor and odor measuring device can be evaluated by comparing the accuracy rate when identifying odors using the sensor elements (E-1) to (E-226) incorporated into the system described below with the accuracy rate when identifying odors using the comparison sensor elements (E'-1) to (E'-17).

[0293] <Measurement method> A housing was fabricated that included an inlet for introducing the sample (odor) and a fan to create airflow so that the sample would spread evenly. An odor sensor (F) was used, in which sensor elements (E-1) to (E-226), each with lead wires soldered to bring terminals to the outside, were housed inside the housing. A comparative odor sensor (F') was also used, in which comparative sensor elements (E'-1) to (E'-17) were housed inside the housing.

[0294] A 1mA constant current power supply and a voltmeter were attached to the ends of the lead wires that were brought out to the outside of the enclosure, and the voltage across both terminals of the lead wires was measured. The voltmeter readings were recorded on a computer.

[0295] The sample was immersed in filter paper so that the concentration of the sample inside the enclosure reached 200 ppm, and the filter paper was inserted through the inlet. Measurement began immediately after inserting the filter paper. 60 seconds after the start of measurement, the fan was rotated again for 60 seconds to expel steam from inside the enclosure while the measurement was performed. Voltage measurements were taken at 0.1-second intervals. The measurement was repeated 100 times under the same conditions.

[0296] The samples used were d-limonene, bornan-2-one, cis-3-hexenol, β-phenylethyl alcohol, citral, L-carbone, γ-undecalactone, eugenol, and linalyl acetate. All samples were manufactured by Tokyo Chemical Industry Co., Ltd.

[0297] <Evaluation Method> The electrical resistance R was calculated using Ohm's law, based on the voltage measured at each time point and the current value of 1 mA supplied from the constant current power supply. The resistance R0 before sample introduction was measured in advance, and R / R0 was calculated.

[0298] The responsiveness of the sensor element to each sample was analyzed using the k-nearest neighbor method, based on the time variation of R / R0 at 0.1-second intervals. The above measurements were performed on the odor sensor (F) and the comparative odor sensor (F'). For each sensor, 100 measurements × 9 samples = 900 measurement data points were randomly divided so that the number of training data points : test data points = 80:20, and a classifier (learning model) was created using the k-nearest neighbor method on the training data. The accuracy rate when classifying the test data for each example and comparative example was used as an indicator of the odor sensor's performance, and a higher accuracy rate indicates higher sensor performance.

[0299] <Evaluation Results> Based on the above measurements, the accuracy rate of odor sensor (F) was 75%, and the accuracy rate of the comparative odor sensor (F') was 31%, indicating that the resin composition according to one embodiment of the present invention and the odor sensor using a sensor element made therefrom have good odor identification performance.

[0300] [Examples 474-699, Comparative Examples 36-52] <Evaluation when using a sample that is a mixture> <Method for preparing a sample that is a mixture> In addition to the individual samples mentioned above, a mixed sample was prepared by the following method: Menthol, benzaldehyde, ethyl acetate, vanillin, hexanal, ethanol, pentyl valerate, linalool, and 2-propanol were each prepared in a desiccator to a gas concentration of 200 ppm to form the mixed raw materials. Next, a 500 mL two-necked round-bottom flask fitted with a three-way stopcock and rubber septum was sealed under vacuum. The following volumes were taken from each mixed raw material using a syringe and injected through the rubber septum of the sealed two-necked round-bottom flask. Mixture sample 1: Menthol (150mL) Benzaldehyde (150 mL) Ethyl acetate (150 mL) Mixture sample 2: Vanillin (150mL) Hexanal (150 mL) Ethanol (150mL) Mixture sample 3: Pentyl valerate (150 mL) Linalool (150mL) 2-Propanol (150 mL) <Measurement method including a sample that is a mixture> Similar to Examples 237-462 and Comparative Examples 18-34, the sensor elements to be evaluated from among the sensor elements (E-1)-(E-226) and comparative sensor elements (E'-1)-(E'-17) were installed inside the housing. The constant current power supply, voltmeter, and computer were also arranged in the same manner.

[0301] A 20 mL sample of the mixture prepared by the method described above was taken with a syringe and injected into the inlet. Measurement was started immediately after the injection of the sample. 60 seconds after the start of measurement, the fan was turned on again for 60 seconds to expel steam from inside the enclosure while measurements were performed. Voltage measurements were taken at 0.1-second intervals. The measurements were repeated 100 times under the same conditions.

[0302] <Evaluation method when using a sample that is a mixture> Using the data obtained by the above method and the data obtained from measurements performed on the individual samples (Examples 237-462, Comparative Examples 18-34), evaluation was performed in the same manner as the evaluation method performed on the individual samples, and the accuracy rate was calculated. That is, the evaluation was performed in the following manner.

[0303] The electrical resistance R was calculated using Ohm's law, based on the voltage measured at each time point and the current value of 1 mA supplied from the constant current power supply. The resistance R0 before sample introduction was measured in advance, and R / R0 was calculated.

[0304] The responsiveness of the sensor element to each sample was analyzed using the k-nearest neighbor method, based on the time variation of R / R0 at 0.1-second intervals. The above measurements were performed on sensor elements (E-1) to (E-226) or comparative sensor elements (E'-1) to (E'-17). A total of 800 measurement data points (100 times x 8 samples) corresponding to each example and comparative example were randomly divided into training data:test data = 80:20, and a classifier (learning model) was created using the k-nearest neighbor method on the training data. The accuracy rate when classifying the test data for each example and comparative example was used as an indicator of the sensor element's performance, with a higher accuracy rate indicating higher sensor performance. In creating the classifier and calculating the accuracy rate for each example, both data obtained from the corresponding sensor element (E) and data obtained from a comparative sensor element (E') using the same polyurethane resin (A) as the sensor element (E) were used.

[0305] <Evaluation results when using a sample that is a mixture> The evaluation results are shown below.

[0306] [Table 28]

[0307] [Table 29]

[0308] [Table 30]

[0309] [Table 31]

[0310] [Table 32]

[0311] [Table 33]

[0312] The accuracy rates calculated in the performance evaluation described above for each of the odor sensors described in Examples 474 to 699 and Comparative Examples 36 to 52 will be compared.

[0313] For example, the accuracy rate of the odor sensor in Example 474, which used sensor element (E-1), was 67%, while the accuracy rate of the odor sensor in Comparative Example 44, which used a comparative sensor element (E'-9) that used the same polyurethane resin as sensor element (E-1), was 40%.

[0314] As shown in Tables 28-33, the accuracy of the odor sensors in Examples 474-699, which used sensor elements (E-1)-(E-226), was higher than that of the odor sensors in Comparative Examples 36-52, which used comparative sensor elements (E'-1)-(E'-17).

[0315] The resin composition according to one embodiment of the present invention and the odor sensor using a sensor element made therefrom can be said to have good odor identification performance even when the sample is a mixture.

[0316] [Manufacturing Example 42] <Preparation of polyester diol (x2)> A reaction vessel equipped with a stirring blade, a stirring device, a nitrogen inlet and outlet was fitted with a heating and cooling device, a thermometer, a temperature control device, a polymerization catalyst introduction tube, and a nitrogen introduction tube. This reaction vessel had a sealing structure that allowed the inside of the reaction vessel to be reduced in pressure. 47.4 parts of 1,4-butanediol and 69.8 parts of adipic acid were added to the reaction vessel, and then 0.5 parts by weight of titanium diisopropoxybistriethanolaminate was added as a polymerization catalyst. The reaction vessel was then heated to 200°C while stirring, and esterification was carried out while distilling off the by-product water while flowing a nitrogen stream until the acid value was 1 or less, yielding polyester diol (x2-12).

[0317] The obtained polyester diol (x2-12) had a hydroxyl value of 53.4, an acid value of 0.2, and a number-average molecular weight of 2100.

[0318] [Manufacturing Example 43] <Preparation of polyurethane resin (A-18)> A reaction vessel equipped with a stirring blade, a stirring device, a nitrogen inlet and outlet was fitted with a heating and cooling device, a thermometer, a temperature control device, a polymerization catalyst introduction tube, and a nitrogen introduction tube. This reaction vessel had a sealing structure that allowed for reduced pressure inside the vessel. 26.6 parts of polyethylene glycol (number average molecular weight 2,000) [product name "PEG-2000" manufactured by Sanyo Chemical Industries, Ltd.] (x1-1) and 1.36 parts of 4,4'- or 2,4'-diphenylmethane diisocyanate (MDI) (y-1) were charged into the reaction vessel and reacted at 60°C for 6 hours under a nitrogen atmosphere to obtain a urethane prepolymer with an NCO content of 3.34% by weight. The NCO content was measured according to JIS K1603-1:2007. Subsequently, after cooling to 40°C, 47 parts of ethyl acetate were added to make a homogeneous solution. Next, 23 parts of isopropanol were added and the mixture was stirred until homogenized. Then, 1.47 parts of isophoronediamine as a chain extender and 0.56 parts of diethanolamine as a reaction stopper were added to the reaction vessel, and the mixture was stirred for another hour. As a result, polyurethane resin (A-18) was obtained. The number-average molecular weight of (A-18) was 13,300.

[0319] The number-average molecular weights of each obtained polyurethane resin (A) were measured by gel permeation chromatography (GPC) under the following conditions, and the results are shown in Table 34.

[0320] Device: HLC-8120 manufactured by Tosoh Corporation Column: One TSK GEL SuperH3000 (manufactured by Tosoh Corporation) and one TSK GEL SuperH4000 (manufactured by Tosoh Corporation) connected together. Measurement temperature: 40℃ Sample solution: 0.25 wt% DMF (dimethylformamide) solution Solution injection volume: 100μl Detection device: Refractive index detector

[0321] [Table 34]

[0322] In Table 1, (y-1) MDI represents 4,4'- or 2,4'-diphenylmethane diisocyanate, (y-2) HDI represents hexamethylene diisocyanate, and (y-3) IPDI represents isophorone diisocyanate.

[0323] Furthermore, the number-average molecular weight was measured by dissolving polyurethane resin (A) in DMF and filtering out the undissolved components using a glass filter to obtain the sample solution.

[0324] [Manufacturing Example 44] <Preparation of polyurethane resin (A-19)> Instead of polyethylene glycol (x1-1), 26.6 parts of polytetramethylene ether glycol (average molecular weight 2000) [product name "PTMG2000" manufactured by Mitsubishi Chemical Corporation] (x1-2) were charged and reacted under a nitrogen atmosphere at 60°C for 6 hours to obtain a urethane prepolymer with an NCO content of 3.34% by weight. Subsequently, after cooling to 40°C, 47 parts of ethyl acetate were added to make a homogeneous solution. Next, 23 parts of isopropanol were added and stirred until homogeneous. Then, 1.47 parts of isophorone diamine as a chain extender and 0.56 parts of diethanolamine as a reaction stopper were added to the reaction vessel, and stirring of the reaction vessel was continued for another hour. As a result, polyurethane resin (A-19) was obtained. The number average molecular weight of (A-19) was 13,000.

[0325] [Manufacturing Example 45] <Preparation of polyurethane resin (A-20)> Instead of polyethylene glycol (x1-1), 26.8 parts of polyester diol (x2-12) synthesized in Production Example 1 were added, and 1.31 parts of MDI (y-1) were added instead of 1.36 parts. The mixture was reacted under a nitrogen atmosphere at 60°C for 6 hours to obtain a urethane prepolymer with an NCO content of 3.22% by weight. Subsequently, after cooling to 40°C, 47 parts of ethyl acetate were added to make a homogeneous solution. Next, 23 parts of isopropanol were added and stirred until homogeneous. Then, 1.41 parts of isophorone diamine as a chain extender and 0.54 parts of diethanolamine as a reaction stopper were added to the reaction vessel, and stirring of the reaction vessel was continued for another hour. As a result, polyurethane resin (A-20) was obtained. The number-average molecular weight of (A-20) was 14,000.

[0326] [Manufacturing Example 46] <Preparation of polyurethane resin (A-21)> 27.0 parts of polyethylene glycol (x1-1) were added instead of 26.6 parts, and 0.93 parts of HDI(y-2) were added instead of MDI(y-1). The mixture was reacted under a nitrogen atmosphere at 110°C for 6 hours to obtain a urethane prepolymer with an NCO content of 3.58% by weight. Subsequently, after cooling to 40°C, 47 parts of ethyl acetate were added to make a homogeneous solution. Next, 23 parts of isopropanol were added and stirred until homogeneous. Then, 1.49 parts of isophorone diamine as a chain extender and 0.57 parts of diethanolamine as a reaction stopper were added to the reaction vessel, and stirring of the reaction vessel was continued for another hour. As a result, polyurethane resin (A-21) was obtained. The number-average molecular weight of (A-21) was 12,500.

[0327] [Manufacturing Example 47] <Preparation of polyurethane resin (A-22)> Instead of polyethylene glycol (x1-1), 27.0 parts of polytetramethylene ether glycol 2000 (x1-2) were added, and instead of MDI (y-1), 0.93 parts of HDI (y-2) were added. The mixture was reacted under a nitrogen atmosphere at 110°C for 6 hours to obtain a urethane prepolymer with an NCO content of 3.58% by weight. Subsequently, after cooling to 40°C, 47 parts of ethyl acetate were added to make a homogeneous solution. Next, 23 parts of isopropanol were added and stirred until homogeneous. Then, 1.49 parts of isophorone diamine as a chain extender and 0.57 parts of diethanolamine as a reaction stopper were added to the reaction vessel, and stirring of the reaction vessel was continued for another hour. As a result, polyurethane resin (A-22) was obtained. The number-average molecular weight of (A-22) was 12,000.

[0328] [Manufacturing Example 48] <Preparation of polyurethane resin (A-23)> Instead of polyethylene glycol (x1-1), 27.1 parts of polyester diol (x2-12) synthesized in Production Example 1 were charged, and instead of MDI (y-1), 0.89 parts of HDI (y-2) were charged. The mixture was reacted under a nitrogen atmosphere at 110°C for 6 hours to obtain a urethane prepolymer with an NCO content of 3.44% by weight. Subsequently, after cooling to 40°C, 47 parts of ethyl acetate were added to make a homogeneous solution. Next, 23 parts of isopropanol were added and stirred until homogeneous. Then, 1.43 parts of isophorone diamine as a chain extender and 0.54 parts of diethanolamine as a reaction stopper were added to the reaction vessel, and stirring of the reaction vessel was continued for another hour. As a result, polyurethane resin (A-23) was obtained. The number-average molecular weight of (A-23) was 13,000.

[0329] [Manufacturing Example 49] <Preparation of polyurethane resin (A-24)> 26.7 parts of polyethylene glycol (x1-1) were added instead of 26.6 parts, and 1.22 parts of IPDI (y-3) were added instead of MDI (y-1). The mixture was reacted under a nitrogen atmosphere at 110°C for 6 hours to obtain a urethane prepolymer with an NCO content of 3.42% by weight. Subsequently, after cooling to 40°C, 47 parts of ethyl acetate were added to make a homogeneous solution. Next, 23 parts of isopropanol were added and stirred until homogeneous. Then, 1.48 parts of isophorone diamine as a chain extender and 0.56 parts of diethanolamine as a reaction stopper were added to the reaction vessel, and stirring of the reaction vessel was continued for another hour. As a result, polyurethane resin (A-24) was obtained. The number-average molecular weight of (A-24) was 12,800.

[0330] [Manufacturing Example 50] <Preparation of polyurethane resin (A-25)> Instead of polyethylene glycol (x1-1), 26.7 parts of polytetramethylene ether glycol 2000 (x1-2) were added, and instead of MDI (y-1), 1.22 parts of IPDI (y-3) were added. The mixture was reacted under a nitrogen atmosphere at 110°C for 6 hours to obtain a urethane prepolymer with an NCO content of 3.42% by weight. Subsequently, after cooling to 40°C, 47 parts of ethyl acetate were added to make a homogeneous solution. Next, 23 parts of isopropanol were added and stirred until homogeneous. Then, 1.48 parts of isophorone diamine as a chain extender and 0.56 parts of diethanolamine as a reaction stopper were added to the reaction vessel, and stirring of the reaction vessel was continued for another hour. As a result, polyurethane resin (A-25) was obtained. The number-average molecular weight of (A-25) was 13,000.

[0331] [Manufacturing Example 51] <Preparation of polyurethane resin (A-26)> Instead of polyethylene glycol (x1-1), 26.9 parts of polyester diol (x2-12) synthesized in Production Example 1 were charged, and instead of MDI (y-1), 1.17 parts of IPDI (y-3) were charged. The mixture was reacted under a nitrogen atmosphere at 110°C for 6 hours to obtain a urethane prepolymer with an NCO content of % by weight. Subsequently, after cooling to 40°C, 47 parts of ethyl acetate were added to make a homogeneous solution. Next, 23 parts of isopropanol were added and stirred until homogeneous. Then, 1.42 parts of isophorone diamine as a chain extender and 0.54 parts of diethanolamine as a reaction stopper were added to the reaction vessel, and stirring of the reaction vessel was continued for another hour. As a result, polyurethane resin (A-26) was obtained. The number-average molecular weight of (A-26) was 13,500.

[0332] [Sensor elements E-237~E-253, comparison sensor elements E'-18, E'-19] <Slurry preparation> Polyurethane resins (A-18) to (A-26), surfactant (B), conductive carbon material (C), and solvent (D) were weighed into glass containers in the amounts listed in Tables 35 and 36 to obtain a mixture. This mixture was stirred at 2000 revolutions per minute for 20 minutes using a rotation / revolution mixer (ARE-310, manufactured by Thinky Co., Ltd.) to obtain a slurry. Resin compositions 1 to 17 were thus obtained as slurries.

[0333] 1.8 parts of polyester diol (x2-12), 1.2 parts of hexadecyltrimethylammonium chloride, 2 parts of SUPER C-65, and 45 parts of N-methylpyrrolidone were weighed into a glass container to obtain a mixture. This mixture was stirred in the same manner as the slurry preparation method described above to obtain a slurry. Thus, resin composition r1 was obtained as the slurry.

[0334] Three parts of polyurethane resin (A-18), two parts of hexadecyltrimethylammonium chloride, and forty-five parts of N-methylpyrrolidone were weighed into a glass container to obtain a mixture. This mixture was stirred in the same manner as the slurry preparation method described above to obtain a slurry. Thus, resin composition r2 was obtained as the slurry.

[0335] <Manufacturing of sensor substrate K-1> A seal substrate (ICB-073, manufactured by Sunhayato Co., Ltd.) with multiple metal wirings spaced 500 μm apart was cut out, containing pairs of metal wirings. The cut seal substrate was then further cut so that the length of the metal wiring was 3.5 cm.

[0336] The cut adhesive substrate was attached to the glass plate using double-sided tape, with the metal wiring facing upwards. Additionally, the excess portion of the metal wiring was masked with vinyl tape so that the exposed portion was 3.0 cm long.

[0337] This allowed us to fabricate the sensor substrate K-1.

[0338] <Sensor element> On the fabricated sensor substrate K-1, resin compositions 1 to 17 and resin compositions r1 and r2 were applied to the exposed parts of the metal wiring using a bar coater (No. 4). After application, the substrate was dried for 3 hours in a circulating air dryer heated to 100°C. After drying, the substrate was cooled to room temperature, and the metal wiring equipped with the odor substance receiving layer 315 was peeled off the glass plate to produce sensor elements (E-237) to (E-253), and comparison sensor elements (E'-18) and (E'-19). The same procedure was repeated 10 times to produce 10 of each sensor element.

[0339] Table 35 shows the substrate type and resin composition for each sensor element (E-237) to (E-253). Table 36 shows the substrate type and resin composition for the comparative sensor elements (E'-18) and (E'-19).

[0340] [Table 35]

[0341] [Table 36]

[0342] <Examples 700-716, Comparative Examples 53, 54> [Fabrication of an odor sensor] A housing was fabricated that included a sample receiving section equipped with an inlet for introducing the sample (odor substance) and an aluminum block constant temperature bath for temperature control, as well as a nitrogen gas cylinder for gas supply, a mass flow controller, and a sensor chamber. Lead wires for bringing terminals to the outside were soldered to each of the 10 sensor elements (E-237), and the 10 sensor elements (E-237) were installed inside the housing. For each sensor element (E-237), a 1mA constant current power supply and a voltmeter for measuring the voltage across both terminals of the lead wire were connected to the end of the lead wire brought outside the housing. In this way, an odor sensor 1 having 10 sensor elements (E-237) was constructed.

[0343] Except for using sensor elements (E-238) to (E-253) and comparative sensor elements (E'-18) and (E'-19) instead of sensor element (E-237), odor sensors 2 to 17 and c1 and c2 were constructed in the same manner as odor sensor 1.

[0344] 〔evaluation〕 [Food Factory Wastewater (Excess Sludge)] 1 liter of excess sludge was collected from Food Factory K. The properties of the excess sludge were pH 6.6, TS 1.6%, SS 1.1%, and organic content 53%. The collected excess sludge was stored in an incubator maintained at 5°C.

[0345] [Measurement of ΔV coefficient of variation - 1] For each of the odor sensors 1-17 and c1 and c2, 5g of the collected excess sludge was placed as a sample in the sample receiving section of the odor sensor. Then, nitrogen as a carrier gas was introduced from the carrier gas inlet into the housing where the sensor elements were installed at a flow rate of 1 L / min using a gas flow regulator and discharged to the outside. During this time, the measured values ​​of the voltmeter connected to the sensor elements were recorded by a computer. In this way, the voltage values ​​of each of the 10 sensor elements in the odor sensor were measured. For each sensor element of each odor sensor, the maximum value ΔV, which is the difference between the output voltage V0 before sample introduction and the voltage V during sample introduction, was calculated. This value was defined as ΔVd=0. In addition, the standard deviation σ and mean value μ of the 10 maximum value ΔV data obtained from each odor sensor were calculated, and the coefficient of variation of ΔV (=σ / μ) of the resin composition forming the sensor element was determined. This value of the coefficient of variation was defined as the ΔVd=0 coefficient of variation.

[0346] After the measurement was completed, the sensor element was removed and placed in a glass desiccator along with 100g of excess sludge collected in a 200ml beaker. The desiccator was left to stand in a 45°C constant temperature bath for 7 days. After 7 days, the sensor element was removed and reattached to the odor sensor. 5g of the collected excess sludge was placed as a sample in the sample receiving section of the odor sensor, and the same measurement was performed to calculate the maximum value ΔV, obtaining ΔVd=7. The ratio of the obtained ΔVd=7 to ΔVd=0 (ΔVd=7 / ΔVd=0) was calculated. In addition, the standard deviation σ and mean value μ of the 10 maximum value ΔV data obtained from each odor sensor were calculated, and the coefficient of variation of ΔV (=σ / μ) of the resin composition forming the sensor element was determined. This value of the coefficient of variation was defined as the ΔVd=7 coefficient of variation.

[0347] Table 37 shows the material composition and physical properties of the resin compositions for odor sensors 1 to 17 in Examples 700 to 716, and odor sensors c1 and c2 in Comparative Examples 53 and 54.

[0348] [Table 37]

[0349] <Consideration> As shown in Table 37, odor sensors 1 to 17 all exhibit ΔV coefficients of variation that are either practically acceptable or practically favorable. Furthermore, it was found that there was no significant difference between the ΔV measured on the first day and the ΔV measured after exposing the sensor elements to a sewage environment of excess sludge for seven days. In addition, it was found that there was no significant difference in the ΔV coefficients of variation of each sensor. From these findings, it was concluded that the sensors are less prone to degradation even when exposed to a humid environment, and the reliability of the measurement results can be ensured.

[0350] A comparison of Examples 700-716 with Comparative Example 53 revealed that odor sensors c1, which has an odor substance receiving layer containing a resin composition without polyurethane resin, showed a larger ΔV coefficient of variation compared to odor sensors 1-17, which have an odor substance receiving layer containing a resin composition containing polyurethane resin, a surfactant, and a conductive carbon material. Furthermore, it was found that ΔV fluctuated significantly before and after exposure to a humid environment, and the ΔV coefficient of variation also increased. Thus, it was found that odor sensors 1-17 have odor substance receiving layers that are more practically preferable than odor sensor c1.

[0351] Furthermore, as described in Comparative Example 54, odor sensor c2, which has an odor substance receiving layer containing a resin composition that does not contain conductive carbon material, was not conductive and therefore could not measure voltage.

[0352] A comparison between Examples 703, 711, and 712 shows that a ΔV coefficient of variation that is practically acceptable can be obtained even when the weight ratio [(A) / (B)] of polyurethane resin (A) to surfactant (B) in the resin composition is different. In particular, the odor sensor 4 equipped with an odor substance receiving layer containing a resin composition with [(A) / (B)] = 1.5 had the smallest ΔV coefficient of variation, and the difference in the ΔV coefficient of variation before and after exposure to a humid environment was also the smallest.

[0353] A comparison between Examples 703 and 713-716 shows that a ΔV coefficient of variation that is practically acceptable can be obtained even when the content of conductive carbon material (C) in the resin composition differs. In particular, the odor sensor 4 equipped with an odor substance receiving layer containing a resin composition with a (C) content of 40% by weight had the smallest ΔV coefficient of variation, and the difference in the ΔV coefficient of variation before and after exposure to a humid environment was also the smallest.

[0354] A comparison between Examples 700 to 708 shows that even when the type of polyisocyanate used in the polyurethane resin contained in the resin composition differs, a ΔV coefficient of variation that is practically acceptable can be obtained. In particular, odor sensors 4 to 6, which have an odor substance receiving layer containing a resin composition containing a polyurethane resin using aliphatic polyisocyanate, had the smallest ΔV coefficient of variation, and the difference in the ΔV coefficient of variation before and after exposure to a humid environment was also the smallest.

[0355] <Examples 717-733, Comparative Examples 55, 56> [Fabrication of an odor sensor] The odor sensors 1-17 and c1, c2 prepared in Examples 700-716 and Comparative Examples 53, 54 were used as is, and the following evaluations were performed.

[0356] 〔evaluation〕 [Sewage (digested sludge)] One liter of digested sludge was collected from the A City treatment plant after digestion. The properties of the digested sludge were pH 7.2, TS 3.0%, SS 2.5%, organic content 74%, and alkalinity 4,350 mg-CaCO3 / L. The collected digested sludge was stored in an incubator maintained at 5°C.

[0357] [Measurement of ΔV coefficient of variation - 2] For each of the odor sensors 1-17 and c1 and c2, 5g of collected digested sludge was placed as a sample in the sample receiving section of the odor sensor. Then, nitrogen as a carrier gas was introduced from the carrier gas inlet into the housing where the sensor elements were installed at a flow rate of 1 L / min using a gas flow regulator and discharged to the outside. During this time, the measured values ​​of the voltmeter connected to the sensor elements were recorded by a computer. In this way, the voltage values ​​of each of the 10 sensor elements in the odor sensor were measured. For each sensor element of each odor sensor, the maximum value ΔV, which is the difference between the output voltage V0 before sample introduction and the voltage V during sample introduction, was calculated. This value was defined as ΔVd=0. In addition, the standard deviation σ and mean value μ of the 10 maximum value ΔV data obtained from each odor sensor were calculated, and the coefficient of variation of ΔV (=σ / μ) of the resin composition forming the sensor element was determined. This value of the coefficient of variation was defined as the ΔVd=0 coefficient of variation.

[0358] After the measurement was completed, the sensor element was removed and placed in a glass desiccator along with 100g of digested sludge collected in a 200ml beaker. The desiccator was left to stand in a 45°C constant temperature bath for 10 days. After 10 days, the sensor element was removed and reattached to the odor sensor. 5g of the collected digested sludge was placed as a sample in the sample receiving section of the odor sensor, and the same measurement was performed to calculate the maximum value ΔV, obtaining ΔVd=10. The ratio of the obtained ΔVd=10 to ΔVd=0 (ΔVd=10 / ΔVd=0) was calculated. In addition, the standard deviation σ and mean value μ of the 10 maximum value ΔV data obtained from each odor sensor were calculated, and the coefficient of variation of ΔV (=σ / μ) of the resin composition forming the sensor element was determined. This value of the coefficient of variation was defined as the ΔVd=10 coefficient of variation.

[0359] Table 38 shows the material composition and physical properties of the resin compositions for odor sensors 1 to 17 in Examples 717 to 733, and odor sensors c1 and c2 in Comparative Examples 55 and 56.

[0360] [Table 38]

[0361] <Consideration> As shown in Table 38, odor sensors 1 to 17 all exhibit ΔV coefficients of variation that are either practically acceptable or practically favorable. Furthermore, it was found that there was no significant difference between the ΔV measured on the first day and the ΔV measured after the sensor elements were exposed to the vapor environment of digested sludge for 10 days. In addition, it was found that there was no significant difference in the ΔV coefficients of variation of each sensor. From these findings, it was concluded that the sensors are less prone to degradation even when exposed to a humid environment, and the reliability of the measurement results can be ensured.

[0362] A comparison between Examples 717-733 and Comparative Example 55 revealed that odor sensors c1, which has an odor substance receiving layer containing a resin composition without polyurethane resin, showed a larger ΔV coefficient of variation compared to odor sensors 1-17, which have an odor substance receiving layer containing a resin composition containing polyurethane resin, a surfactant, and a conductive carbon material. Furthermore, it was found that ΔV fluctuated significantly before and after exposure to a humid environment, and the ΔV coefficient of variation also increased. Thus, odor sensors 1-17 were found to have a more practically preferable odor substance receiving layer than odor sensor c1.

[0363] Furthermore, as described in Comparative Example 56, odor sensor c2, which has an odor substance receiving layer containing a resin composition that does not contain conductive carbon material, was not conductive and therefore could not measure voltage.

[0364] A comparison between Examples 720, 728, and 729 shows that a ΔV coefficient of variation that is practically acceptable can be obtained even when the weight ratio [(A) / (B)] of polyurethane resin (A) to surfactant (B) in the resin composition is different. In particular, the odor sensor 4 equipped with an odor substance receiving layer containing a resin composition with [(A) / (B)] = 1.5 had the smallest ΔV coefficient of variation, and the difference in the ΔV coefficient of variation before and after exposure to a humid environment was also the smallest.

[0365] A comparison between Examples 720 and 730-733 shows that a ΔV coefficient of variation that is practically acceptable can be obtained even when the content of conductive carbon material (C) in the resin composition differs. In particular, the odor sensor 4 equipped with an odor substance receiving layer containing a resin composition with a (C) content of 40% by weight had the smallest ΔV coefficient of variation, and the difference in the ΔV coefficient of variation before and after exposure to a humid environment was also the smallest.

[0366] A comparison between Examples 717 to 725 shows that even when the type of polyisocyanate used in the polyurethane resin contained in the resin composition differs, a ΔV coefficient of variation that is practically acceptable can be obtained. In particular, odor sensors 4 to 6, which have an odor substance receiving layer containing a resin composition containing a polyurethane resin using aliphatic polyisocyanate, had the smallest ΔV coefficient of variation, and the difference in the ΔV coefficient of variation before and after exposure to a humid environment was also the smallest.

[0367] <Examples 734-750, Comparative Examples 57, 58> [Fabrication of an odor sensor] A housing was fabricated that included an inlet for introducing the sample (odor substance), a fan for generating airflow, and a sensor chamber. Lead wires for bringing terminals to the outside were soldered to each of the 10 sensor elements (E-237), and the 10 sensor elements (E-237) were installed inside. For each sensor element (E-237), a 1mA constant current power supply and a voltmeter for measuring the voltage across both terminals of the lead wire were connected to the end of the lead wire brought to the outside of the housing. In this way, an odor sensor 18 having 10 sensor elements (E-237) was constructed.

[0368] Except for using sensor elements (E-238) to (E-253) and comparative sensor elements (E'-18) and (E'-19) instead of sensor element (E-237), odor sensors 19 to 34 and c3 and c4 were constructed in the same manner as odor sensor 18.

[0369] 〔evaluation〕 [Concentrated wastewater from chemical plants (industrial wastewater)] The concentrated wastewater discharged from Sanyo Chemical Industries, Ltd.'s Kyoto Plant was used as the sample.

[0370] [Measurement of ΔV coefficient of variation - 3] For each of the odor sensors 18-34 and c3 and c4, piping was connected from the concentrated waste liquid tank to the sample inlet of the odor sensor. Then, an airflow generating fan was activated to flow the vapor of the concentrated waste liquid into the housing where the sensor elements were installed and discharged to the outside. During this time, the readings from the voltmeter connected to the sensor elements were recorded by a computer. In this way, the voltage values ​​of each of the 10 sensor elements in the odor sensor were measured. For each sensor element of each odor sensor, the maximum value ΔV, which is the difference between the output voltage V0 before sample introduction and the voltage V during sample introduction, was calculated. This value was set to ΔVd = 0.

[0371] The airflow generating fan was kept running, measurements were continued, and the maximum value ΔV after 30 days was calculated, yielding ΔVd=30. The ratio of the obtained ΔVd=30 to ΔVd=0 (ΔVd=30 / ΔVd=0) was determined. In addition, the standard deviation σ and mean value μ of the 10 maximum value ΔV data obtained from each odor sensor were calculated, and the coefficient of variation of ΔV (=σ / μ) of the resin composition forming the sensor element was determined. This value of the coefficient of variation was defined as the ΔVd=30 coefficient of variation.

[0372] Table 39 shows the material composition and physical properties of the resin compositions for odor sensors 18-34 in Examples 734-750 and odor sensors c3 and c4 in Comparative Examples 57 and 58.

[0373] [Table 39]

[0374] <Consideration> As shown in Table 39, odor sensors 1 to 17 all exhibit ΔV coefficients of variation that are either practically acceptable or practically favorable. Furthermore, it was found that there was no significant difference between the ΔV measured on the first day and the ΔV measured after the sensor elements were exposed to the chemical plant wastewater environment for 30 days. In addition, it was found that there was no significant difference in the ΔV coefficients of variation for each sensor. From these findings, it was concluded that the sensors are less prone to degradation even when exposed to a humid environment, and the reliability of the measurement results can be ensured.

[0375] A comparison of Examples 734-750 with Comparative Example 57 revealed that odor sensors c1, which has an odor substance receiving layer containing a resin composition without polyurethane resin, showed a larger ΔV coefficient of variation compared to odor sensors 1-17, which have an odor substance receiving layer containing a resin composition containing polyurethane resin, a surfactant, and a conductive carbon material. Furthermore, it was found that ΔV fluctuated significantly before and after exposure to a humid environment, and the ΔV coefficient of variation also increased. Thus, it was found that odor sensors 1-17 have odor substance receiving layers that are more practically preferable than odor sensor c1.

[0376] Furthermore, as described in Comparative Example 58, odor sensor c2, which has an odor substance receiving layer containing a resin composition that does not contain conductive carbon material, was not conductive and therefore could not measure voltage.

[0377] A comparison between Examples 737, 745, and 746 shows that a ΔV coefficient of variation that is practically acceptable can be obtained even when the weight ratio [(A) / (B)] of polyurethane resin (A) to surfactant (B) in the resin composition is different. In particular, the odor sensor 4 equipped with an odor substance receiving layer containing a resin composition with [(A) / (B)] = 1.5 had the smallest ΔV coefficient of variation, and the difference in the ΔV coefficient of variation before and after exposure to a humid environment was also the smallest.

[0378] A comparison between Examples 737 and 747-750 shows that a ΔV coefficient of variation that is practically acceptable can be obtained even when the content of conductive carbon material (C) in the resin composition differs. In particular, the odor sensor 4 equipped with an odor substance receiving layer containing a resin composition with a (C) content of 40% by weight had the smallest ΔV coefficient of variation, and the difference in the ΔV coefficient of variation before and after exposure to a humid environment was also the smallest.

[0379] A comparison between Examples 734 to 742 shows that even when the type of polyisocyanate used in the polyurethane resin contained in the resin composition differs, a ΔV coefficient of variation that is practically acceptable can be obtained. In particular, odor sensors 4 to 6, which have an odor substance receiving layer containing a resin composition containing a polyurethane resin using aliphatic polyisocyanate, had the smallest ΔV coefficient of variation, and the difference in the ΔV coefficient of variation before and after exposure to a humid environment was also the smallest.

[0380] As described above, the odor sensor element for water quality evaluation containing polyurethane resin accurately detected odors emitted from wastewater and raw water for water purification compared to the sensor element without polyurethane resin. Furthermore, the odor sensor element for water quality evaluation containing polyurethane resin showed more stable measurement performance in environments exposed to moisture compared to the sensor element without polyurethane resin.

[0381] In particular, it was found that a water quality evaluation odor sensor element using a polyurethane resin (A) composed of aromatic polyisocyanate can accurately measure odors emitted from wastewater and raw water for water purification. [Industrial applicability]

[0382] This invention is useful as an odor identification sensor for water quality management used in industry and daily life. For example, it can be used for water quality management of raw water for purification. It is also possible to acquire changes in the odor of wastewater from factories, etc., in combination with changes in the water quality of the wastewater (for example, values ​​such as pH and COD). Such data can be useful in determining what kind of purification treatment is necessary for wastewater, or in determining whether or not the equipment for performing the purification treatment needs to be operated. [Explanation of Symbols]

[0383] 10, 10a Estimation device 11 Measurement value acquisition unit (acquisition unit) 12. Change Pattern Analysis Unit (Analysis Unit) 16 Estimation part 30 Odor Sensor 31, 31b Sensor elements 32 Constant voltage power supply (power supply) 33. Voltmeter (measuring instrument) 100, 100a Odor measuring device 313A, 313C 1st metal wiring 313B, 313D 2nd metal wiring 315, 315c, 315d Odor substance receiving layer

Claims

1. First metal wiring and, A second metal wiring is spaced apart from the first metal wiring, A fragrance substance receiving layer is in contact with at least a portion of the first metal wiring and at least a portion of the second metal wiring, and comprises a resin composition containing a polyurethane resin (A), a surfactant (B), and a conductive carbon material (C), Equipped with, The polyurethane resin (A) contains an aromatic polyisocyanate. Odor sensor element for water quality evaluation.

2. The odor sensor element for water quality evaluation according to claim 1, wherein the surfactant (B) has an HLB value of 8 to 18.

3. The odor sensor element for water quality evaluation according to claim 1, wherein the weight ratio [(A) / (B)] of the polyurethane resin (A) to the surfactant (B) is 1.0 to 4.

0.

4. The content of the conductive carbon material (C) is the polyurethane resin (A) and the surfactant. (B) and the conductive carbon material (C) together amount to 5 to 75% by weight. The odor sensor element for water quality evaluation according to claim 1.

5. A water quality evaluation odor sensor element according to any one of claims 1 to 4, A power supply for supplying power to the odor sensor element for water quality evaluation, A measuring device that outputs a measurement value indicating the electrical conductivity of the odor substance receiving layer of a water quality evaluation odor sensor element powered by the aforementioned power supply, A water quality evaluation odor sensor equipped with the following features.

6. The water quality evaluation odor sensor according to claim 5, wherein the power supply supplies a constant current or applies a constant voltage to the at least one water quality evaluation odor sensor element.

7. A water quality evaluation apparatus comprising a water quality evaluation odor sensor and estimation device according to claim 5, The estimation device is, An acquisition unit that acquires the measured value from the aforementioned measuring instrument, An analysis unit for analyzing the change in electrical conductivity over time of at least one odor sensor element for water quality evaluation, It comprises an estimation unit that estimates evaluation results for a target gas emitted from the water being evaluated based on an estimation model, The estimation model is generated by machine learning using training data that includes a combination of analysis results obtained for each of the multiple types of target gases when the target gas is brought into contact with at least one water quality evaluation odor sensor element, and identification information of the target gas. Water quality evaluation device.

8. A control program for causing a computer to function as a water quality evaluation device according to claim 7. The acquisition unit, the analysis unit, and the estimation unit are configured to function as computers. A control program for that purpose.

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