Detector, sensor element set, sensitive membrane set, polymer composition set, evaluation method and selection method

Abstract

To provide a detector having high identification accuracy.SOLUTION: A detector comprises a plurality of sensor elements. Each of the plurality of sensor elements includes: a sensitive membrane containing a polymer; and a measurement part including the sensitive membrane on its surface, capable of measuring characteristic values reflecting a change in a physical parameter caused by adsorption of a substance onto the sensitive membrane. The polymers contained in the sensitive membranes of the plurality of sensor elements have compositions different from each other. When water vapor is adsorbed onto the sensitive membranes of the plurality of sensor elements and a water adsorption test for measuring characteristic values is performed, a coefficient of variation of the characteristic value is 0.2 or less. When acetic acid water vapor is adsorbed onto the sensitive membranes of the plurality of sensor elements and an acetic acid adsorption test for measuring characteristic values is performed, a coefficient of variation of the characteristic value is 0.5 or more. When butylamine vapor is adsorbed onto the sensitive membranes of the plurality of sensor elements and a butylamine adsorption test for measuring the characteristic value is performed, a coefficient of variation of the characteristic value is 1.5 or more.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a detection device; a sensor element set, a sensitive film set, and a polymer composition set for producing the detection device; a method for evaluating the detection device; and a method for selecting a sensitive film for use in the detection device. [Background technology]

[0002] Detection devices such as odor detection devices are used for various purposes. For example, odor detection devices are known that detect gas substances generated by spoilage of food and control the quality of food in a refrigerator. In addition, odor detection devices are known that are used for quality control and sensory evaluation of food and flavorings. Specific examples of such detection devices are described in Patent Documents 1 to 7. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 6883306 [Patent Document 2] Patent Publication No. 2021-32842 [Patent Document 3] Patent Publication No. 2021-21613 [Patent Document 4] International Publication No. 2021-256460 [Patent Document 5] International Publication No. 2021-261271 [Patent Document 6] Patent No. 6556870 [Patent Document 7] Patent No. 6973772 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the detection devices described in Patent Documents 1 to 5 have low discrimination accuracy. For example, since the output value when a certain gas substance is detected is close to the output value when a different gas substance is detected, it may be difficult to accurately discriminate and detect the two gas substances. Therefore, the range of detectable gas substances may be limited.

[0005] If a detection device uses olfactory cells of a living organism as described in Patent Documents 6 and 7 and is equipped with as many sensor elements as the olfactory cells of the living organism, it is expected that the accuracy of identification will be improved. However, a detection device equipped with such a large number of sensor elements is not realistic because the production and operation costs are excessive.

[0006] Therefore, there is a demand for the development of a new detection device with high identification accuracy.

[0007] In addition, no method has been proposed to objectively evaluate the identification accuracy of a detection device. Therefore, when selecting a sensitive film to be provided in a detection device, there is no objective selection criterion for the sensitive film, making it difficult to select an appropriate sensitive film.

[0008] The present invention has been devised in consideration of the above-mentioned problems, and aims to provide a detection device with high discrimination accuracy; a sensor element set, a sensitive film set, and a polymer composition set capable of manufacturing a detection device with high discrimination accuracy; a method for evaluating the discrimination accuracy when a detection device detects a substance; and a method for selecting a sensitive film for use in a detection device. [Means for solving the problem]

[0009] The present inventor has conducted intensive research to solve the above-mentioned problems. As a result, the present inventor has found that in a detection device that detects a substance based on a characteristic value reflecting a change in a physical parameter caused by the adsorption of the substance to the sensitive film, an improvement in the discrimination accuracy is achieved when a combination of sensitive films is selected such that the coefficient of variation of the characteristic value for water vapor, the coefficient of variation of the characteristic value for acetic acid vapor, and the coefficient of variation of the characteristic value for butylamine vapor are each within a range equal to or greater than a specific value. The present inventor has also found that an objective evaluation of discrimination accuracy is possible by using a new evaluation index value called the degree of separation using principal component analysis. Furthermore, the present inventor has found that by utilizing this degree of separation, a combination of sensitive films to be used in the detection device can be appropriately selected. The present invention has been completed based on such findings. Thus, the present invention includes the following.

[0010] <1> A detection device comprising a plurality of sensor elements; Each of the plurality of sensor elements includes a sensitive film containing one or more polymers, and a measurement unit having the sensitive film on a surface thereof and capable of measuring a characteristic value reflecting a change in a physical parameter caused by adsorption of a substance to the sensitive film; The sensitive films of the plurality of sensor elements have different compositions; When a water adsorption test is performed in which water vapor is adsorbed on the sensitive films of a plurality of sensor elements to measure the characteristic values, the coefficient of variation of the characteristic values ​​is 0.2 or more; When an acetic acid adsorption test is performed in which acetic acid vapor is adsorbed on the sensitive films of a plurality of sensor elements to measure a characteristic value, the coefficient of variation of the characteristic value is 0.5 or more; A detection device in which, when a butylamine adsorption test is conducted in which butylamine vapor is adsorbed onto the sensitive films of a plurality of sensor elements and a characteristic value is measured, the coefficient of variation of the characteristic value is 1.5 or more. <2> The sensitive films of the plurality of sensor elements include two or more selected from the group consisting of a cyclic structure-containing polymer, a hydrocarbon-based polymer, a fluorine-based polymer, and a silicone-based polymer; <1> The detection device according to claim 1 . <3> At least one of the sensitive films of the plurality of sensor elements contains two or more selected from the group consisting of a cyclic structure-containing polymer, a hydrocarbon-based polymer, a fluorine-based polymer, and a silicone-based polymer; <1> or <2> The detection device according to claim 1 . <4> The measurement unit includes a piezoelectric element. <1> ~ <3> 13. The detection device according to any one of claims 1 to 12. <5> A sensor element set including a plurality of sensor elements each including a sensitive film containing one or more polymers, and a measurement unit having the sensitive film on a surface thereof and capable of measuring a characteristic value reflecting a change in a physical parameter caused by adsorption of a substance to the sensitive film, comprising: The sensitive films of the plurality of sensor elements have different compositions; When a water adsorption test is performed in which water vapor is adsorbed on the sensitive films of a plurality of sensor elements to measure the characteristic values, the coefficient of variation of the characteristic values ​​is 0.2 or more; When an acetic acid adsorption test is performed in which acetic acid vapor is adsorbed on the sensitive films of a plurality of sensor elements to measure a characteristic value, the coefficient of variation of the characteristic value is 0.5 or more; A sensor element set in which, when a butylamine adsorption test is conducted in which butylamine vapor is adsorbed onto the sensitive films of a plurality of sensor elements to measure the characteristic values, the coefficient of variation of the characteristic values ​​is 1.5 or more. <6> A sensitive membrane set including a plurality of sensitive membranes each including one or more polymers; The multiple sensitive films have different compositions; a plurality of sensor elements are prepared by providing each sensitive film on the surface of a measurement part capable of measuring a characteristic value reflecting a change in a physical parameter caused by the adsorption of a substance onto the sensitive film, and when a water adsorption test is performed in which water vapor is adsorbed onto the sensitive films of the plurality of sensor elements and the characteristic value is measured, the coefficient of variation of the characteristic value is 0.2 or more; When an acetic acid adsorption test is performed in which acetic acid vapor is adsorbed on the sensitive films of the plurality of sensor elements to measure a characteristic value, the coefficient of variation of the characteristic value is 0.5 or more; A sensitive membrane set, in which, when a butylamine adsorption test is conducted in which butylamine vapor is adsorbed onto the sensitive membranes of the plurality of sensor elements to measure a characteristic value, the coefficient of variation of the characteristic value is 1.5 or more. <7> A polymer composition set comprising a plurality of polymer compositions comprising one or more polymers and a solvent; the plurality of polymer compositions have different compositions from one another; a plurality of sensor elements are prepared, each comprising a sensitive film formed by applying and drying a polymer composition, and a measurement unit having the sensitive film on its surface and capable of measuring a characteristic value reflecting a change in a physical parameter caused by the adsorption of a substance onto the sensitive film; when a water adsorption test is performed in which water vapor is adsorbed onto the sensitive films of the plurality of sensor elements and the characteristic value is measured, the coefficient of variation of the characteristic value is 0.2 or more; When an acetic acid adsorption test is performed in which acetic acid vapor is adsorbed on the sensitive films of the plurality of sensor elements to measure a characteristic value, the coefficient of variation of the characteristic value is 0.5 or more; A polymer composition set, wherein when a butylamine adsorption test is conducted in which butylamine vapor is adsorbed onto the sensitive films of the plurality of sensor elements to measure characteristic values, the coefficient of variation of the characteristic values ​​is 1.5 or more. <8> A method for evaluating a detection device having a plurality of sensor elements, comprising: Each of the plurality of sensor elements includes a sensitive film and a measurement unit having the sensitive film on a surface thereof and capable of measuring a characteristic value reflecting a change in a physical parameter caused by adsorption of a substance to the sensitive film; a first step of adsorbing a first substance onto the sensitive films of a plurality of sensor elements and measuring characteristic values ​​thereof to obtain multi-dimensional measurement data including information on the characteristic values; a second step of causing a second substance to be adsorbed on the sensitive films of the plurality of sensor elements to measure characteristic values, thereby obtaining multi-dimensional measurement data including information on the characteristic values; A third step of performing a principal component analysis on the measurement data measured in the first step and the measurement data measured in the second step to calculate scores of two principal components; a fourth step of calculating, in a coordinate system having axes of the two principal components, a first probability ellipse including points having a score corresponding to a first material at a specific probability density, and a second probability ellipse including points having a score corresponding to a second material at the specific probability density; A fifth step of calculating a degree of separation D represented by the following formula (M1) from the first probability ellipse and the second probability ellipse; (c) evaluation methods; D=L' / L (M1) (In formula (M1), L represents the distance between the center of the first density ellipse and the center of the second density ellipse, L' represents the distance between the point where the line segment connecting the center of the first probability ellipse and the center of the second probability ellipse intersects with the first probability ellipse and the point where the line segment intersects with the second probability ellipse. <9> A method for selecting a sensitive film for detecting each of substances belonging to a substance group from a plurality of sensitive film candidates having different compositions; The selection method is providing a candidate sensitive film on a surface of a measurement unit capable of measuring a characteristic value reflecting a change in a physical parameter caused by the adsorption of a substance onto the candidate sensitive film to obtain a plurality of sensor elements; a step of adsorbing a substance belonging to a substance group onto the candidate sensitive films of a plurality of sensor elements and measuring characteristic values ​​thereof to obtain multi-dimensional measurement data including information on the characteristic values; performing a principal component analysis of the measurement data to calculate scores of two principal components; Calculating the degree of separation D between every two substances belonging to the substance group from the scores; selecting a sensitive membrane from a plurality of sensitive membrane candidates based on a degree of separation D; The calculation method for the degree of separation D is as follows: calculating a first probability ellipse including points indicated by scores corresponding to one of the two substances at a specific probability density in a coordinate system having axes of the two principal components, and a second probability ellipse including points indicated by scores corresponding to the other of the two substances at the specific probability density; A selection method comprising: a step of calculating a degree of separation D, represented by the following formula (M1), from the first probability ellipse and the second probability ellipse. D=L' / L (M1) (In formula (M1), L represents the distance between the center of the first density ellipse and the center of the second density ellipse, L' represents the distance between the point where the line segment connecting the center of the first probability ellipse and the center of the second probability ellipse intersects with the first probability ellipse and the point where the line segment intersects with the second probability ellipse. Effect of the Invention

[0011] The present invention aims to provide a detection device with high discrimination accuracy; a sensor element set, a sensitive film set, and a polymer composition set capable of manufacturing a detection device with high discrimination accuracy; a method for evaluating the discrimination accuracy when a detection device detects a substance; and a method for selecting a sensitive film for use in a detection device. [Brief description of the drawings]

[0012] [Figure 1] FIG. 1 is a schematic diagram showing a detection device according to a first embodiment of the present invention. [Diagram 2] FIG. 2 is a graph showing a change in an output value converted from a physical parameter measured by a measuring unit in one example. [Diagram 3] FIG. 3 is a two-dimensional map for explaining analysis by principal component analysis according to the first embodiment of the present invention. [Figure 4] FIG. 4 is a two-dimensional map showing a score pattern representing the first principal component score and the second principal component score calculated in the third step of the evaluation method according to the second embodiment of the present invention. [Diagram 5] FIG. 5 is a two-dimensional map showing the score patterns of the first principal component score and the second principal component score calculated in Example 1 of the present invention. [Figure 6] FIG. 6 is a two-dimensional map showing the score patterns of the first principal component scores and the second principal component scores calculated in Example 2 of the present invention. [Figure 7] FIG. 7 is a two-dimensional map showing the score pattern of the first principal component score and the second principal component score calculated in Example 3 of the present invention. [Figure 8] FIG. 8 is a two-dimensional map showing the score pattern of the first principal component score and the second principal component score calculated in Example 4 of the present invention. [Figure 9]FIG. 9 is a two-dimensional map showing the score pattern of the first principal component score and the second principal component score calculated in Example 5 of the present invention. [Figure 10] FIG. 10 is a two-dimensional map showing the score pattern of the first principal component score and the second principal component score calculated in Example 6 of the present invention. [Figure 11] FIG. 11 is a two-dimensional map showing the score pattern of the first principal component score and the second principal component score calculated in Comparative Example 1 of the present invention. [Figure 12] FIG. 12 is a two-dimensional map showing the score pattern of the first principal component score and the second principal component score calculated in Comparative Example 2 of the present invention. [Figure 13] FIG. 13 is a two-dimensional map showing the score pattern of the first principal component score and the second principal component score calculated in Comparative Example 3 of the present invention. [Figure 14] FIG. 14 is a two-dimensional map showing the score pattern of the first principal component score and the second principal component score calculated in Comparative Example 4 of the present invention. [Figure 15] FIG. 15 is a two-dimensional map showing the score pattern of the first principal component score and the second principal component score calculated in Comparative Example 5 of the present invention. [Figure 16] FIG. 16 is a two-dimensional map showing the score pattern of the first principal component score and the second principal component score calculated in Comparative Example 6 of the present invention. [Figure 17] FIG. 17 is a two-dimensional map showing the score pattern of the first principal component score and the second principal component score calculated in Comparative Example 7 of the present invention. [Figure 18] FIG. 18 is a two-dimensional map showing the score pattern of the first principal component score and the second principal component score calculated in Comparative Example 8 of the present invention. [Figure 19] FIG. 19 is a two-dimensional map showing the score pattern of the first principal component score and the second principal component score calculated in Comparative Example 9 of the present invention. [Figure 20] FIG. 20 is a two-dimensional map showing the score pattern of the first principal component score and the second principal component score calculated in Comparative Example 10 of the present invention. [Figure 21] FIG. 21 is a two-dimensional map showing the score pattern of the first principal component score and the second principal component score calculated in Comparative Example 11 of the present invention. [Figure 22] FIG. 22 is a two-dimensional map showing the score pattern of the first principal component score and the second principal component score calculated in Comparative Example 12 of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] The present invention will be described in detail below with reference to the following embodiments and examples. However, the present invention is not limited to the following embodiments and examples, and may be modified and implemented as desired without departing from the scope of the claims and their equivalents.

[0014] In the following description, the term "adsorption" includes not only physical adsorption but also adsorption by chemical bonds or biochemical actions, unless otherwise specified.

[0015] <Description of the embodiment relating to the detection device> FIG. 1 is a schematic diagram showing a detection device 10 according to a first embodiment of the present invention. As shown in FIG. 1, the detection device 10 according to the first embodiment of the present invention includes a plurality of sensor elements 100A, 100B, 100C, 100D, and 100E. A combination of the plurality of sensor elements 100A to 100E may be referred to as a "sensor element set" below. In this embodiment, a detection device 10 including five sensor elements 100A to 100E will be described as an example, but the number of sensor elements may be four or less, or six or more. Usually, the detection device 10 includes an element mounting section 200, and the sensor elements 100A to 100E are provided on the element mounting section 200. The detection device 10 may include an output section 300 that can output information on characteristic values ​​detected by the sensor elements 100A to 100E.

[0016] The multiple sensor elements 100A to 100E include measurement sections 110A to 110E and sensitive films 120A to 120E provided on the surfaces of the measurement sections 110A to 110E, respectively. A combination of the multiple sensitive films 120A to 120E may be hereinafter referred to as a "sensitive film set."

[0017] The measuring units 110A to 110E are provided so as to be able to measure characteristic values ​​reflecting changes in physical parameters caused by the adsorption of a substance to the sensitive films 120A to 120E. As the measuring units 110A to 110E, typically, elements capable of measuring characteristic values ​​reflecting changes in physical parameters caused by the sensitive films 120A to 120E formed on the measuring units 110A to 110E due to the adsorption of a substance to the sensitive films 120A to 120E are used. The physical parameters are not particularly limited, and examples thereof include surface stress, stress, surface tension, pressure, mass, elasticity, Young's modulus, Poisson's ratio, resonant frequency, frequency, phase, volume, thickness, viscosity, density, magnetic force, magnetic quantity, magnetic field, magnetic flux, magnetic flux density, electrical resistance, electrical quantity, dielectric constant, power, electric field, charge, current, voltage, electric potential, mobility, electrostatic energy, capacitance, inductance, reactance, susceptance, admittance, impedance, conductance, plasmon, refractive index, absorption wavelength, absorbance, luminous intensity, and temperature.

[0018] Examples of the measuring units 110A to 110E include transducers such as piezoelectric elements, surface plasmon resonance elements (SPR elements), field effect transistor elements (FET elements), surface acoustic wave elements, charge coupled elements, metal oxide semiconductor elements, organic conductive polymer elements, electrochemical elements, etc. The piezoelectric elements may include quartz crystal oscillators (QCM).

[0019] A piezoelectric element usually includes a piezoelectric body made of a piezoelectric material and electrodes provided on the piezoelectric body. Examples of the piezoelectric material include piezoelectric single crystals such as quartz crystal and lithium niobate; piezoelectric ceramics such as lead zirconate titanate, barium titanate and lead titanate; and piezoelectric polymer films such as vinylidene fluoride and trifluoroethylene copolymer. The sensitive films 120A to 120E may be provided on the surface of the piezoelectric body of the piezoelectric element, or on the surface of the electrodes.

[0020] The surface plasmon resonance element usually includes a prism and a metal layer formed on the prism. Examples of materials for the metal layer include gold, silver, etc. The sensitive films 120A to 120E are usually provided on the surface of the metal layer of the surface plasmon resonance element.

[0021] The characteristic values ​​measured by the measuring units 110A to 110E may be selected from values ​​reflecting changes in physical parameters caused by the adsorption of a substance to the sensitive films 120A to 120E. The characteristic values ​​may be, for example, the amount of change (magnitude of change) of the physical parameter, the time of change of the physical parameter (the time from the start of the change to the maximum amount of change, the time from the start of the change to the end of the change, etc.), the rate of change of the physical parameter (amount of change per unit time), etc.

[0022] Furthermore, since the change in the output value converted from the physical parameter generally reflects the change in the physical parameter, a value reflecting the change in the output value may be adopted as the characteristic value. Thus, the characteristic value may be, for example, the amount of change in the output value (magnitude of change), the time of change in the output value (the time from the start of the change until the output value becomes maximum, the time from the start of the change until the change ends, etc.), the rate of change in the output value (amount of change per unit time), etc. Here, the term "conversion" includes not only changing the unit but also deriving an output value corresponding to the value of the physical parameter by performing a calculation.

[0023] Examples of the output value include a dimensionless value obtained by dividing the measured value of a physical parameter by the reference value of the physical parameter, a value obtained by subtracting the measured value of a physical parameter by the reference value of the parameter, etc. Examples of the reference value include a value of a physical parameter measured by the measuring units 110A-110E having a reference substance (nitrogen, water, etc.) adsorbed thereon, a value of a physical parameter measured by the measuring units 110A-110E in a state in which the sensitive films 120A-120E are formed and no substance to be measured is adsorbed thereon, etc.

[0024] Other examples of the output value include a value obtained by removing noise (e.g., signals below a predetermined threshold) from the measurement value of the physical parameter, a value obtained by removing abnormal values ​​(e.g., signals above a predetermined threshold) from the measurement value of the physical parameter, and a value obtained by averaging the measurement values ​​of the physical parameter over a predetermined short period of time.

[0025] When the output value is used, the measuring units 110A to 110E may include a calculation unit (not shown) capable of calculating the output value. In the following, an example will be described in which the amount of change in the output value converted from the physical parameter is used as the "characteristic value".

[0026] Each of the sensitive films 120A to 120E contains one or more polymers. The sensitive films 120A to 120E have compositions different from one another. Here, when a certain sensitive film "has a composition different from one another," the following is included. (1) The polymers contained in the sensitive film have different compositions. (2) The additives contained in the sensitive film other than the polymer have different compositions.

[0027] (1) The composition of the polymers contained in the sensitive films (for example, the first sensitive film and the second sensitive film) is "different" from each other in the following sense. (1-1) When the first sensitive film contains only one type of polymer and the second sensitive film contains only one type of polymer, the compositions of the polymer of the first sensitive film and the polymer of the second sensitive film are "different from each other" means that the chemical structure of the polymer of the first sensitive film and the chemical structure of the polymer of the second sensitive film are different. (1-2) When the first sensitive film contains two or more types of polymers and the second sensitive film contains two or more types of polymers, the compositions of the polymers in the first sensitive film and the polymers in the second sensitive film are "different from each other" means that (i) the blending ratio of the polymers contained in the first sensitive film is different from the blending ratio of the polymers contained in the second sensitive film, (ii) the chemical structure of at least one type of polymer contained in the first sensitive film is different from the chemical structure of any of the polymers contained in the second sensitive film, or (iii) the chemical structure of at least one type of polymer contained in the second sensitive film is different from the chemical structure of any of the polymers contained in the first sensitive film. (1-3) When the first sensitive film contains only one type of polymer and the second sensitive film contains two or more types of polymer, the compositions of the polymer in the first sensitive film and the polymer in the second sensitive film are considered to be "different from each other."

[0028] (2) The composition of the additives contained in the sensitive films being "different" from one another includes differences in the chemical structure and / or amount of the additives.

[0029] In particular, it is preferable that (1) the polymers contained in the sensitive films 120A to 120E have compositions different from one another.

[0030] The sensitive films 120A to 120E are selected so as to satisfy the following requirements (I), (II), and (III) in combination. (I) When a water adsorption test is performed in which water vapor is adsorbed on the sensitive films 120A to 120E and a characteristic value reflecting a change in a physical parameter is measured, the coefficient of variation of the characteristic value is 0.2 or more. (II) When an acetic acid adsorption test is performed in which acetic acid vapor is adsorbed on the sensitive films 120A to 120E and a characteristic value reflecting a change in a physical parameter is measured, the coefficient of variation of the characteristic value is 0.5 or more. (III) When a butylamine adsorption test is performed in which butylamine vapor is adsorbed on the sensitive films 120A to 120E to measure a characteristic value reflecting a change in a physical parameter, the coefficient of variation of the characteristic value is 1.5 or more.

[0031] Requirement (I) will be described in detail below. Requirement (I) indicates that the coefficient of variation of the characteristic value obtained when a water adsorption test is performed using the detection device 10 is within a specific range. In the water adsorption test, water vapor is adsorbed on the sensitive films 120A-120E of the sensor elements 100A-100E, and characteristic values ​​reflecting changes in physical parameters caused by the adsorption are measured by the measuring units 110A-110E. In the example shown in this embodiment, five sensor elements 100A-100E are used, so information on five characteristic values ​​is obtained: the characteristic value X(A) measured by the sensor element 100A, the characteristic value X(B) measured by the sensor element 100B, the characteristic value X(C) measured by the sensor element 100C, the characteristic value X(D) measured by the sensor element 100D, and the characteristic value X(E) measured by the sensor element 100E. Therefore, the average value and standard deviation of these characteristic values ​​X(A)-X(E) are calculated, and the standard deviation is divided by the average value to obtain a coefficient of variation.

[0032] When the amount of change in the output value converted from the physical parameter is used as the characteristic value as in the example shown in this embodiment, the water adsorption test may be performed as follows. That is, in the water adsorption test, water vapor may be adsorbed on the sensitive films 120A-120E and the physical parameters may be measured once or twice or more times. In this case, the magnitude of change in the output value converted from the physical parameters in each measurement may be used as the "amount of change in the output value" as a characteristic value, and its coefficient of variation may be calculated. Alternatively, the average of the magnitude of change in the output value converted from the physical parameter measured two or more times may be used as the "amount of change in the output value" as the characteristic value to determine the coefficient of variation. For example, the physical parameter is measured 30 times to obtain 30 measurement results of the magnitude of change in the output value converted from the physical parameter for each of the sensor elements 100A to 100E. From the 30 measurement results, the average of the magnitude of change is calculated for each of the sensor elements 100A to 100E. The coefficient of variation may be calculated using five pieces of information on the average magnitude of change thus obtained as information on the characteristic value measured by the five sensor elements 100A to 100E. When the coefficient of variation is determined by measuring the physical parameter two or more times, the influence of fluctuations in the measured value can be suppressed, and the accuracy of the coefficient of variation can be improved.

[0033] The range of the coefficient of variation measured in the water adsorption test is, in detail, usually 0.2 or more, preferably 0.3 or more, and more preferably 0.4 or more. There is no particular upper limit, and the upper limit may be, for example, 3.0 or less, 2.0 or less, or 1.0 or less.

[0034] Water vapor adsorbed in a water adsorption test represents a neutral gas substance. Therefore, obtaining a coefficient of variation in the above range in a water adsorption test indicates that a wide range of information on the adsorption properties of neutral gas substances can be obtained by the sensor elements 100A to 100E. Moreover, water vapor is widely present in the general environment. Therefore, when the detection device 10 is used, it may be inevitably affected by water vapor in the detection atmosphere. In general, when a gas substance is adsorbed to the sensitive film, the adsorption of the gas substance may be hindered by water vapor, or the adsorbed gas substance may be expelled by water vapor. Therefore, when the sensitive films 120A-120E have a coefficient of variation within the above range in a water adsorption test, it may be possible to obtain information on the change in physical parameters due to the interaction between the gas substance and water vapor, as well as the adsorption of the gas substance to the sensitive films 120A-120E, from the amount of change. Furthermore, if the water adsorption test gives a coefficient of variation in the range mentioned above, it may be possible to obtain information for distinguishing between gaseous substances based on differences in their hydrophilic and hydrophobic properties. Therefore, if a large coefficient of variation within the above range is obtained in a water adsorption test, it is possible to widen the range of information that can be obtained when using the detection device 10, thereby contributing to improving the accuracy of identifying gas substances.

[0035] Requirement (II) will be described in detail below. Requirement (II) indicates that the coefficient of variation of the characteristic value obtained when an acetic acid adsorption test is performed using the detection device 10 is within a specific range. In the acetic acid adsorption test, acetic acid vapor is adsorbed on the sensitive films 120A-120E of the sensor elements 100A-100E, and characteristic values ​​reflecting changes in physical parameters caused by the adsorption are measured by the measuring units 110A-110E. In the example shown in this embodiment, five sensor elements 100A-100E are used, so as in the water adsorption test, information on five characteristic values ​​is obtained: the characteristic value X(A) measured by the sensor element 100A, the characteristic value X(B) measured by the sensor element 100B, the characteristic value X(C) measured by the sensor element 100C, the characteristic value X(D) measured by the sensor element 100D, and the characteristic value X(E) measured by the sensor element 100E. Therefore, the average value and standard deviation of these characteristic values ​​X(A)-X(E) are calculated, and the standard deviation is divided by the average value to obtain a coefficient of variation.

[0036] When the amount of change in the output value converted from the physical parameter is used as the characteristic value as in the example shown in this embodiment, the following may be performed in the acetic acid adsorption test. That is, in the acetic acid adsorption test, the acetic acid vapor may be adsorbed on the sensitive films 120A-120E and the physical parameters may be measured once or twice or more times. In this case, the magnitude of the change in the output value converted from the physical parameters in each measurement may be used as the "amount of change in the output value" as a characteristic value, and the coefficient of variation may be calculated. Also, the average of the magnitude of change in the output value converted from physical parameters measured two or more times may be used as the "amount of change in the output value" as a characteristic value to determine its coefficient of variation. As with the water adsorption test, when the coefficient of variation is determined by performing two or more measurements in the acetic acid adsorption test, the effect of fluctuation in the measured values ​​can be suppressed and the accuracy of the coefficient of variation can be improved.

[0037] The range of the coefficient of variation measured in the acetic acid adsorption test is, in detail, usually 0.5 or more, preferably 0.6 or more, and more preferably 0.7 or more. There is no particular upper limit, and the upper limit may be, for example, 3.0 or less, 1.5 or less, or 2.0 or less.

[0038] The acetic acid vapor adsorbed in the acetic acid adsorption test represents an acidic gas substance or a structural portion of a gas substance that exhibits acidity. Therefore, obtaining a coefficient of variation in the above range in the acetic acid adsorption test indicates that the sensor elements 100A to 100E can obtain a wide range of information regarding the adsorption properties of acidic gas substances and gas substances having structural portions that exhibit acidity. Therefore, when a large coefficient of variation in the above range is obtained in the acetic acid adsorption test, it is possible to widen the range of information obtained when using the detection device 10, which can contribute to improving the identification accuracy of gas substances.

[0039] Requirement (III) will be described in detail below. Requirement (III) indicates that the coefficient of variation of the characteristic value obtained when a butylamine adsorption test is performed using the detection device 10 is within a specific range. In the butylamine adsorption test, butylamine vapor is adsorbed on the sensitive films 120A-120E of the sensor elements 100A-100E, and characteristic values ​​reflecting changes in physical parameters caused by the adsorption are measured by the measuring units 110A-110E. In the example shown in this embodiment, five sensor elements 100A-100E are used, so as in the water adsorption test, information on five characteristic values ​​is obtained: the characteristic value X(A) measured by the sensor element 100A, the characteristic value X(B) measured by the sensor element 100B, the characteristic value X(C) measured by the sensor element 100C, the characteristic value X(D) measured by the sensor element 100D, and the characteristic value X(E) measured by the sensor element 100E. Therefore, the average value and standard deviation of these characteristic values ​​X(A)-X(E) are calculated, and the standard deviation is divided by the average value to obtain a coefficient of variation.

[0040] When the amount of change in the output value converted from the physical parameter is used as the characteristic value as in the example shown in this embodiment, the following procedure may be used in the butylamine adsorption test. That is, in the butylamine adsorption test, butylamine vapor may be adsorbed on the sensitive films 120A-120E and the physical parameters may be measured once or twice or more times. In this case, the magnitude of change in the output value converted from the physical parameters in each measurement may be used as the "amount of change in the output value" as a characteristic value, and the coefficient of variation may be calculated. Also, the average of the magnitude of change in the output value converted from physical parameters measured two or more times may be used as the "amount of change in the output value" as a characteristic value to determine its coefficient of variation. As with the water adsorption test, when the coefficient of variation is determined by performing two or more measurements in the butylamine vapor adsorption test, the effect of fluctuation in the measured values ​​can be suppressed and the accuracy of the coefficient of variation can be improved.

[0041] The range of the coefficient of variation measured in the butylamine adsorption test is, in detail, usually 1.5 or more, preferably 1.6 or more, and more preferably 1.7 or more. There is no particular upper limit, and the upper limit may be, for example, 4.0 or less, 3.5 or less, or 3.0 or less.

[0042] Butylamine vapor adsorbed in the butylamine adsorption test represents a basic gas substance or a structural portion that shows the basicity of the gas substance. Therefore, obtaining a coefficient of variation in the above range in the butylamine adsorption test indicates that the sensor elements 100A to 100E can obtain a wide range of information regarding the adsorption properties of basic gas substances and gas substances having structural portions that show basicity. Therefore, when a large coefficient of variation in the above range is obtained in the butylamine adsorption test, it is possible to widen the range of information that can be obtained when using the detection device 10, which can contribute to improving the identification accuracy of gas substances.

[0043] The water adsorption test, acetic acid adsorption test, and butylamine adsorption test can be usually performed in a test environment in the atmosphere at normal temperature and normal pressure (23°C, 1 atm). In addition, when the environment in which the detection device 10 is used is known, the water adsorption test, acetic acid adsorption test, and butylamine adsorption test may be performed in the same test environment as the environment in which the detection device is used. The water adsorption test, acetic acid adsorption test, and butylamine adsorption test may be performed in a test environment with any relative humidity, but from the viewpoint of performing a more appropriate evaluation, it is preferable to perform the test in a relative humidity range in which the detection device is frequently used. The specific relative humidity range is preferably 40% RH or more, more preferably 50% RH or more, and preferably 80% RH or less, more preferably 70% RH or less.

[0044] The water adsorption test, the acetic acid adsorption test, and the butylamine adsorption test are tests performed to determine whether or not the above-mentioned requirements (I), (II), and (III) are satisfied. Therefore, a detection device that satisfies the requirements (I), (II), and (III) when the water adsorption test, the acetic acid adsorption test, and the butylamine adsorption test are performed is included in the scope of the present invention, regardless of whether or not the above tests are performed.

[0045] From the viewpoint of satisfying the combination of the above-mentioned requirements (I) to (III), it is preferable that the sensitive films 120A to 120E are formed using polymers having different main chain chemical structures. The significance of applying such polymers having different main chain chemical structures will be explained below in comparison with the conventional technology. However, the technical scope of the present invention is not limited to the following explanation.

[0046] In conventional detection devices, various functional groups or side chains are often introduced into the polymer forming the sensitive film, and the type of gas substance to be detected is adjusted by the type of functional group or side chain. Specifically, on the premise that the gas substance is adsorbed to the sensitive film by interaction with the functional group or side chain, the type of gas substance to be adsorbed is adjusted by the type of functional group or side chain. In general, the functional group and side chain introduced as described above can appear on the surface of the sensitive film. Therefore, conventional detection devices have been developed based on the technical idea of ​​causing a change in physical parameters by adsorption of the gas substance to the surface of the sensitive film, and detecting the gas substance based on the change.

[0047] However, the inventors' investigations revealed that gaseous substances not only adsorb onto the surface of the sensitive film, but also penetrate into the inside of the sensitive film and are adsorbed therein. Therefore, when a gaseous substance is adsorbed onto the sensitive film, (i) Adsorption of a gaseous substance onto the surface of the sensitive membrane causes a change in a physical parameter; (ii) the gaseous substance penetrates into the sensitive membrane and is adsorbed therein, causing a change in a physical parameter; and (iii) A change in a physical parameter occurs due to a combination of the adsorption of a gaseous substance on the surface of the sensitive film and the adsorption of a gaseous substance that has penetrated into the inside of the sensitive film. It is possible.

[0048] The adsorption of gaseous substances into the inside of the sensitive membrane is generally greatly affected by the solubility and diffusion degree of the gaseous substance in the polymer. Therefore, the adsorption of gaseous substances into the inside of the sensitive membrane is greatly affected not only by functional groups or side chains, but also by the main chain structure of the polymer, which can mainly determine the solubility and diffusion degree. Therefore, when the sensitive membranes 120A-120E are formed using polymers with different main chain chemical structures, it is possible to measure characteristic values ​​that reflect changes in the physical parameters (i) as well as (ii) and (iii). Therefore, the range of measurable characteristic values ​​can be increased depending on the combination of polymers contained in the sensitive membranes 120A-120E, so that the coefficient of variation obtained in the above-mentioned water adsorption test, acetic acid adsorption test, and butylamine adsorption test can be increased.

[0049] The polymers contained in the sensitive films 120A to 120E may have different functional groups. The type of functional group may be one type, or two or more types. Furthermore, there is no limit to the concentration and ratio of these functional groups.

[0050] Preferable polymers include, for example, cyclic structure-containing polymers, hydrocarbon-based polymers, fluorine-based polymers, and silicone-based polymers. Note that these polymer classifications are not exclusive, and a certain polymer may belong to multiple classifications.

[0051] The cyclic structure-containing polymer refers to a polymer containing a cyclic structure such as an aliphatic carbon ring, an aliphatic heterocycle, an aromatic carbon ring, and an aromatic heterocycle in its molecular structure. The cyclic structure-containing polymer may contain a cyclic structure in its main chain, may contain a cyclic structure in its side chain, or may contain a cyclic structure in both its main chain and its side chain. For example, a polymer containing a cyclic structure in its main chain tends to have a rigid molecular structure. The rigidity of the molecular structure generally affects the size of the free volume and the degree of diffusion of gas substances. Therefore, when a sensitive film containing a polymer containing a rigid molecular structure is combined with a sensitive film containing a polymer containing a flexible molecular structure, the difference in adsorption between the sensitive films can be increased, and the above-mentioned coefficient of variation can be increased.

[0052] The term "hydrocarbon polymer" refers to a polymer containing a hydrocarbon skeleton such as an aliphatic hydrocarbon skeleton, an aromatic hydrocarbon skeleton, or an alicyclic hydrocarbon skeleton in its molecular structure. The hydrocarbon polymer may contain a hydrocarbon skeleton in its main chain, may contain a hydrocarbon skeleton in its side chain, or may contain a hydrocarbon skeleton in both its main chain and its side chain. For example, a polymer that contains an aliphatic hydrocarbon skeleton in its main chain and does not contain a cyclic structure in its main chain tends to have a flexible molecular structure. In addition, a polymer that contains a hydrocarbon skeleton usually has low intramolecular polarity. Therefore, when a sensitive film containing a polymer that contains a flexible molecular structure is combined with a sensitive film containing a polymer that contains a rigid molecular structure or a polymer that contains a polar functional group, the difference in adsorptivity between the sensitive films can be increased, and the above-mentioned coefficient of variation can be increased.

[0053] Fluorine-based polymer refers to a polymer that contains fluorine atoms in its molecular structure. Fluorine-based polymers generally tend to have low surface free energy. Therefore, when a sensitive film containing a polymer with low surface free energy is combined with a sensitive film containing a polymer with high surface free energy, the difference in adsorption between the sensitive films can be increased, and the above-mentioned coefficient of variation can be increased.

[0054] Silicone-based polymer refers to a polymer containing a siloxane skeleton in its molecular structure. Silicone-based polymers may contain a siloxane skeleton in their main chain, may contain a siloxane skeleton in their side chain, or may contain a siloxane skeleton in both their main chain and side chain. Silicone-based polymers generally contain a molecular skeleton different from that of polymers containing a carbon skeleton that are widely used. Therefore, silicone-based polymers may differ from polymers containing a carbon skeleton in the interactions between polymer molecular chains that affect the solubility and diffusion of gas molecules. Therefore, when a sensitive film containing a silicone-based polymer is combined with a sensitive film containing a polymer containing a carbon skeleton, the difference in adsorptivity between the sensitive films can be increased, and the above-mentioned coefficient of variation can be increased.

[0055] The sensitive films 120A to 120E preferably contain two or more polymers selected from the group consisting of a ring-containing polymer, a hydrocarbon-based polymer, a fluorine-based polymer, and a silicone-based polymer. In this case, one or more of the sensitive films 120A to 120E may contain a polymer selected from the group, and another one or more of the sensitive films 120A to 120E may contain another polymer selected from the group. Furthermore, at least one of the sensitive films 120A to 120E may contain two or more polymers selected from the group.

[0056] Specific examples of the polymer include phenoxy polymers such as a polymer represented by the following formula (P-1); polystyrenes such as a polymer represented by formula (P-2), formula (P-3) or formula (P-4); cycloolefin polymers such as a polymer represented by formula (P-5); phenolic polymers such as a polymer represented by formula (P-6); sulfur-containing polymers such as a polymer represented by formula (P-7); polyimides such as a polymer represented by formula (P-8); ester polymers such as a polymer represented by formula (P-9) or formula (P-10); urethane-based polymers such as the polymer represented by formula (P-12); polyacrylic-based polymers such as the polymer represented by formula (P-13); pyridine ring-containing polymers such as the polymer represented by formula (P-14), formula (P-15) or formula (P-16); cellulose-based polymers such as the polymer represented by formula (P-17); siloxane-based polymers such as the polymer represented by formula (P-18); and fluorine-based polymers such as the polymer represented by formula (P-19).

[0057] [ka]

[0058] [ka]

[0059] (In formulas (P-1) to (P-19), R 1 represents an alkyl group; R2 and R 3 each independently represents an alkylene group; R 4 , R 5 and R 6 each independently represents a hydrogen atom or an ethyl group; R 7 , R 8 , R 9 and R 10 each independently represents an alkyl group; X represents a halogen atom; and n, n1, n2, and n3 each independently represent a natural number corresponding to the repeating number.

[0060] The above-mentioned polymer may have a side chain as necessary. In addition, the above-mentioned polymer may have a functional group and / or an unsaturated bond introduced at one or more positions among the main chain, the main chain end, the side chain and the side chain end. Examples of the functional group that may be introduced include a hydroxyl group and an amino group. Examples of the unsaturated bond that may be introduced include a double bond and a triple bond. The type of the functional group and the unsaturated bond to be introduced may be one type or two or more types. Furthermore, there is no limit to the concentration and ratio of those functional groups and unsaturated bonds.

[0061] The specific compositions (types, compounding ratios, etc.) of the polymers contained in the sensitive films 120A-120E can be selected so as to satisfy the combination of the above-mentioned requirements (I)-(III). In particular, it is preferable to select the compositions of the polymers contained in the sensitive films 120A-120E so as to obtain a large separation degree D according to the types of gas substances to be detected by the detection device 10.

[0062] The weight average molecular weight Mw of the above-mentioned polymer is preferably 1000 or more, more preferably 2000 or more, particularly preferably 3000 or more, and is preferably 1 million or less, more preferably 500,000 or less, particularly preferably 300,000 or less. The weight average molecular weight can be measured as a polystyrene-equivalent value by gel permeation chromatography (GPC).

[0063] The amount of polymer contained in the sensitive films 120A to 120E can be appropriately set so as to satisfy a combination of the above-mentioned requirements (I) to (III). In one example, the mass of the polymer contained in one sensitive film is preferably 10% or more, more preferably 30% or more, and even more preferably 50% or more, relative to 100% mass of the sensitive film. The upper limit is usually 100% or less, and may be, for example, 99% or less, 98% or less, or 97% or less by mass.

[0064] The sensitive films 120A to 120E may contain additives as optional components in combination with the polymer. Examples of additives include compatibilizers, surface modifiers, crosslinking agents, crosslinkable resins, curing agents, curing catalysts, organic fillers, inorganic fillers, inorganic particles, conductive resins, conductive particles, thermally conductive resins, thermally conductive particles, porous substances, biosubstances, biomimetic substances, solvents, softeners, tackifiers, moisture absorbents, metal complexes, inclusion compounds, compounds capable of forming coordinate bonds, and compounds capable of forming ionic bonds. One type of additive may be used alone, or two or more types may be used in combination at any ratio.

[0065] The thickness of the sensitive films 120A-120E can be appropriately set within a range in which gas substances can be detected. The specific thickness range of the sensitive films is preferably 1 nm to 50 μm, and more preferably 50 nm to 35 μm. The thicknesses of the multiple sensitive films 120A-120E may be the same or different.

[0066] There is no particular restriction on the manufacturing method of the sensitive films 120A to 120E as long as the desired sensitive films 120A to 120E can be obtained. For example, each of the sensitive films 120A to 120E can be manufactured by a method including the steps of preparing a liquid polymer composition containing a polymer and a solvent, applying the polymer composition to the surface of the measurement section, and drying the applied polymer composition. Since a plurality of sensitive films 120A to 120E are manufactured, a plurality of polymer compositions are usually used. Hereinafter, the combination of a plurality of polymer compositions may be referred to as a "polymer composition set."

[0067] The polymer composition includes a polymer and a solvent, and may further include optional components such as additives as necessary. In the polymer composition, the polymer and optional components may be dispersed in a solvent, but from the viewpoint of extending the pot life of the polymer composition, it is preferable that they are dissolved in a solvent. As the solvent, an inorganic solvent such as water may be used, an organic solvent may be used, or an inorganic solvent and an organic solvent may be used in combination. Among them, it is preferable to use an organic solvent as the solvent. Examples of preferred organic solvents include n-heptanol, dimethyl sulfoxide, decahydronaphthalene, methyl benzoate, N-methylpyrrolidone, γ-butyrolactone, 1,2,3,4-tetrahydronaphthalene (also known as tetralin), carbitol acetate, 1,3-dimethyl-2-imidazolidinone, butyl carbitol, propyl benzoate, diethylene glycol, 4-tert-butyl methyl benzoate, butyl carbitol acetate, 1-butanol, 2-pentanol, methyl cellosolve, propylene glycol-1-monomethyl ether-2-acetate, ethyl lactate, methyl amyl ketone, cyclohexanone, dimethylacetamide, mesitylene, etc. The solvent may be used alone or in combination of two or more.

[0068] The polymer composition can be produced, for example, by mixing a polymer and a solvent, and, if necessary, any optional components. The order of mixing the components is not limited. In addition, in order to promote dissolution or dispersion of the polymer and any optional components in the solvent, any optional treatment such as stirring or heat treatment may be performed.

[0069] After preparing the polymer composition, the polymer composition is applied to the surface of the measurement part. The application method is not particularly limited. The application may be performed, for example, using a dispenser. In the application using a dispenser, the polymer composition stored in a syringe is usually discharged through a needle, and the discharged polymer composition is attached to the surface of the measurement part, thereby performing the application. The application method using a dispenser can suppress waste of the polymer composition, and further does not require a mask, so that it is excellent in cost and productivity. By this application, a film of the polymer composition can be formed on the surface of the measurement part.

[0070] After the polymer composition is applied, the applied film of the polymer composition is dried. By drying, the solvent is removed from the film of the polymer composition, and a sensitive film can be formed. There is no limitation on the drying method. For example, the drying can be performed by heat drying. In one example, the heating temperature in heat drying is preferably 60° C. or higher, more preferably 80° C. or higher, and even more preferably 100° C. or higher, and is preferably 250° C. or lower, more preferably 200° C. or lower, and even more preferably 180° C. or lower. The heating time is preferably 1 minute to 5 hours, more preferably 10 minutes to 3 hours, and even more preferably 20 minutes to 2 hours.

[0071] When the polymer composition contains a crosslinking agent, a crosslinkable resin, or a curing agent as an optional component, crosslinking or curing may proceed by heat during drying. When crosslinking or curing proceeds, a sensitive film containing a crosslinked or cured polymer can be obtained.

[0072] The element mounting part 200 is provided so as to be able to support the sensor elements 100A to 100E. In this embodiment, an example will be described in which the element mounting part 200 is formed with an opening 210 so that a sample gas can be supplied to the sensitive films 120A to 120E of the sensor elements 100A to 100E.

[0073] The element mounting section 200 may be provided with an element for extracting information on characteristic values ​​that reflect changes in the physical parameters of the sensitive films 120A-120E detected by the sensor elements 100A-100E.

[0074] For example, when the measuring units 110A-110E are piezoelectric elements, the piezoelectric elements can usually detect changes in the physical parameters of the sensitive films 120A-120E as changes in the vibration frequency of the piezoelectric elements. Therefore, in order to extract a characteristic value reflecting this change in frequency, the element mounting unit 200 may include elements such as wiring (not shown) for applying a voltage to vibrate the piezoelectric elements and a frequency meter (not shown) for measuring the vibration frequency of the piezoelectric elements.

[0075] Furthermore, for example, when the measuring units 110A-110E are surface plasmon resonance elements, the surface plasmon resonance elements can usually detect changes in the physical parameters of the sensitive films 120A-120E as changes in resonance angle. Therefore, the element mounting unit 200 may include elements such as a light source (not shown) for irradiating the surface plasmon resonance element with light and a photodetector (not shown) for detecting reflected light from the surface plasmon resonance element in order to extract a characteristic value reflecting the change in resonance angle.

[0076] The output unit 300 is provided so as to be able to output information sent from the sensor elements 100A-100E provided in the element mounting part 200. Examples of the output unit 300 include a display device capable of displaying information on a screen, and an interface capable of outputting information to a computer device.

[0077] Next, a description will be given of a detection method for detecting a gas substance from a sample gas using the above-mentioned detection device 10. In the following description, the gas substance to be detected using the detection device 10 may be referred to as a "target substance."

[0078] The detection method according to this embodiment includes a step of supplying a sample gas to the sensor elements 100A-100E. A target substance in the supplied sample gas comes into contact with and is adsorbed by the sensitive films 120A-120E of the sensor elements 100A-100E. This adsorption causes a change in a physical parameter of the sensitive films 120A-120E. A characteristic value reflecting this change in the physical parameter is measured by the measurement units 110A-110E of the sensor elements 100A-100E.

[0079] For example, when the measuring units 110A-110E are piezoelectric elements, the change in the physical parameters of the sensitive films 120A-120E can be detected as a change in vibration frequency by the piezoelectric elements. Therefore, a value reflecting the change in the vibration frequency can be measured as the characteristic value. Also, for example, when the measuring units 110A-110E are surface plasmon resonance elements, the change in the physical parameters of the sensitive films 120A-120E can be detected as a change in resonance angle by the surface plasmon resonance elements. Therefore, a value reflecting the change in resonance angle can be measured as the characteristic value.

[0080] FIG. 2 is a graph showing the change in the output value converted from the physical parameters measured by the measuring units 110A-110E in one example. In FIG. 2, the output values ​​obtained by the measuring units 110A-110E are shown as curves with the reference symbols 120A-120E of the sensitive films included in the measuring units 110A-110E. When the change in the output value converted from the physical parameters is adopted as the characteristic value as in the example shown in this embodiment, the measuring units 110A-110E may measure the physical parameters and obtain the output value by converting the physical parameters. Normally, during the period in which the sample gas is supplied, the adsorption of the target substance to the sensitive films 120A-120E progresses, so the change in the physical parameters increases, and therefore the change in the output value also increases. Furthermore, normally, after the supply of the sample gas is stopped, the target substance desorbs from the sensitive films 120A-120E, so the change in the physical parameters decreases, and therefore the change in the output value also decreases. Therefore, a peak generally appears in the measured output value. Typically, the difference is calculated by subtracting the initial value of the output value from the output value at the extreme value (maximum or minimum value) of the peak, and this difference is used as the characteristic value "amount of change in the output value." Here, the initial value of the output value refers to the output value before the supply of the sample gas. In addition, if it is desired to further improve the accuracy, two or more measurements may be performed to obtain two or more differences, and the average of these two or more differences may be used as the amount of change.

[0081] In the example shown in this embodiment, five sensor elements 100A-100E equipped with sensitive films 120A-120E having different compositions are used. Therefore, five characteristic values ​​X(A), X(B), X(C), X(D) and X(E) corresponding to the sensitive films 120A-120E are obtained. Information on these characteristic values ​​X(A)-X(E) is usually converted into an electrical signal and sent to the output section 300.

[0082] The output section 300 outputs the information of the transmitted characteristic values ​​X(A) to X(E). By analyzing this output information, it is possible to detect the target substance. The analysis can be performed, for example, by multivariate analysis, and is preferably performed by principal component analysis. When performing the analysis by principal component analysis, the number of principal components may be three or more, but two is preferable. By mapping the score patterns of the principal components, the target substance can be easily detected.

[0083] A specific example of principal component analysis will be described below. The target substance to be detected is detected in advance using the detection device 10, and information on the characteristic value is obtained. For distinction, this information may be referred to as "standard information" hereinafter. In the example shown in this embodiment, standard information on five characteristic values ​​corresponding to the five sensitive films 120A to 120E is obtained, and five-dimensional measurement data including the standard information is obtained. Usually, the detection device 10 is used to detect a plurality of target substances, and thus five-dimensional measurement data including standard information is obtained for each of the plurality of target substances. Using these measurement data, principal component analysis is performed to obtain the principal components and the ranges of the scores of the principal components (principal component scores). For example, when analysis is performed using two principal components, the first principal component and the second principal component, principal component analysis is performed on the measurement data to obtain the first principal component and the second principal component and the ranges of their scores (first principal component score and second principal component score). The obtained first principal component and second principal component and the ranges of their scores are recorded.

[0084] The principal components thus prepared using the standard information are used to analyze the information on the characteristic values ​​X(A)-X(E) obtained from the sample gas. Specifically, the principal component scores in the system prepared using the standard information are calculated from five-dimensional measurement data including the information on the characteristic values ​​X(A)-X(E). Then, if the principal component scores obtained from the characteristic values ​​X(A)-X(E) are within the range of principal component scores that a certain target substance should have, it can be determined that the sample gas contains that target substance, and the target substance can be detected.

[0085] The principal component analysis shown in the above specific example is easy to understand if a two-dimensional map using a coordinate system with the principal components obtained from the standard information as axes is used. Therefore, an example of a two-dimensional map using the coordinate system will be shown and explained. Figure 3 is a two-dimensional map for explaining the analysis by the principal component analysis according to the first embodiment of the present invention.

[0086] In FIG. 3, the range of scores that three target substances T1, T2, and T3 should have is shown by a dashed ellipse E in a coordinate system with the axes of two principal components (in this example, the first principal component (PC1) and the second principal component (PC2)) obtained from the standard information. T1 , E T2 and E T3 An example is shown in Fig. 3. The first and second principal component scores in this coordinate system are calculated from five-dimensional measurement data including information on characteristic values ​​X(A) to X(E) obtained from the sample gas. Point P represented by the first and second principal component scores calculated in this way is plotted in the coordinate system shown in Fig. 3. The plotted point P is then fitted to an ellipse E T1 If it is in the ellipse E T1 Since it can be determined that the target substance T1 corresponding to the target substance T1 was contained in the sample gas, detection of the target substance T1 can be achieved.

[0087] In this embodiment, an example is shown in which the first and second principal components are used as the two principal components, but the combination of the principal components is not limited to the above. For example, the detection may be performed by adopting a combination of the first and third principal components, or a combination of the second and third principal components.

[0088] According to the detection device 10 and detection method of this embodiment, a single detection device 10 can detect multiple types of target substances with high identification accuracy. For example, since the difference between the principal component score obtained when one target substance is detected and the principal component score obtained when another target substance is detected can be made large, it is possible to accurately identify those target substances. As a specific example, in a two-dimensional map such as the example shown in FIG. 3, the range in which point P appears when target substance T1 is detected, the range in which point P appears when target substance T2 is detected, and the range in which point P appears when target substance T3 is detected can be clearly separated. Thus, an ellipse E indicating the range of scores that target substances T1, T2, and T3 should have can be formed. T1 , E T2 and E T3 Therefore, it is possible to clearly distinguish between the target substances T1, T2, and T3. According to the detection device 10 and the detection method of the present embodiment, the above-mentioned advantages can be obtained when detecting a wide range of target substances.

[0089] In addition, the detection device 10 of this embodiment has a simple structure, so the device can be made smaller. Furthermore, the detection device 10 has fewer environmental restrictions than devices that use olfactory cells of a living body, so it can be used in a wide range of environments. Furthermore, the detection device 10 can perform detection by simple adsorption of gaseous substances, so detection can be performed in a short period of time. Therefore, it is possible to meet needs in terms of size, environment, and detection time that conventional devices could not meet, and the inspection device 10 can be used in a more practical and wide range of areas.

[0090] The detection device 10 and the detection method may be modified from the embodiment described above. For example, in the example shown in the above embodiment, the amount of change in the output value converted from the physical parameter is used as the "characteristic value", but a value other than the amount of change may be used as the characteristic value. As a specific example, the change time from when the output value starts to change until it reaches the extreme value may be used as the characteristic value. Also, for example, the change rate in the period from when the output value starts to change until it reaches the extreme value may be used as the characteristic value. This change rate can be represented by the slope of a curve showing the output value before it reaches the extreme value in the graph shown in FIG. 2, so the differential value of the curve before it reaches the extreme value may be used as the characteristic value. Furthermore, for example, the change rate in the period from when the output value reaches the extreme value until it returns to the initial value may be used as the characteristic value. This change rate can be represented by the slope of a curve showing the output value after it reaches the extreme value in the graph shown in FIG. 2, so the differential value of the curve after it reaches the extreme value may be used as the characteristic value. Also, for example, the integral value obtained by integrating the output value with respect to time may be used as the characteristic value.

[0091] Also, instead of obtaining one characteristic value from one measurement, two or more measurements may be performed to obtain one characteristic value. For example, two or more measurements may be performed to obtain two or more amounts of change in the output value converted from the physical parameters, and the average of these two or more amounts of change may be used as the characteristic value. In this case, the detection accuracy of the target substance can be improved.

[0092] When performing two or more measurements as described above, the device or measurement environment may not be stable during the first to several measurements, resulting in large noise. In this case, the measurement results from the first to an appropriate number of measurements, in which the device or measurement environment is not stable, may be excluded, and the characteristic value may be obtained from the measurement results from the subsequent measurements.

[0093] In the example shown in the above embodiment, the characteristic value is calculated from the output value converted from the physical parameter, but the characteristic value may be calculated from the physical parameter itself. Therefore, as in the case of the characteristic value calculated from the output value, for example, a curve showing the physical parameter may be drawn on a graph with the physical parameter on the vertical axis and time on the horizontal axis, and the differential value or integral value of the curve may be used as the characteristic value.

[0094] Furthermore, instead of the characteristic values ​​themselves measured by the measuring units 110A-110E, values ​​calculated from the characteristic values ​​may be used as "measurement data including information on characteristic values". For example, the above analysis may be performed using standardized values ​​of the characteristic values ​​as "measurement data including information on characteristic values". As a specific example, the average value and standard deviation may be calculated from the characteristic values ​​X(A)-X(E), and the difference between each characteristic value and the average value may be divided by the standard deviation to obtain a value (standardized value) that may be used as "measurement data including information on characteristic values". When standardization is used in this way, the effect of variations in detection conditions for each detection operation can be eliminated, making it possible to more easily detect the target substance.

[0095] In addition, although the above-described embodiment shows an example in which five sensor elements 100A to 100E are used, the number of sensor elements may be four or less, or six or more. The upper limit of the number of sensor elements is not particularly limited, and may be, for example, 1000 or less, 500 or less, 100 or less, etc.

[0096] The measurement of the measurement data by the detection device 10 and the analysis of the measurement data may be performed at the same time or at different times. Furthermore, the measurement of the measurement data by the detection device 10 and the analysis of the measurement data may be performed at the same location or at different locations.

[0097] <Explanation of the method for evaluating the discrimination accuracy of the detection device> In general, when a target substance is detected using a detection device, the characteristic value may fluctuate slightly each time a measurement is performed. Therefore, when a target substance is detected using principal component analysis as described above, the score of the principal components may usually fluctuate. Due to the influence of this fluctuation, it has been difficult to objectively evaluate the discrimination accuracy of a detection device in the past. In response to this, the present inventor has developed an evaluation method that can objectively evaluate the discrimination accuracy of the above-mentioned detection device using an index called "separation degree D" when the number of principal components is two. This will be explained below.

[0098] The evaluation method according to the second embodiment of the present invention is a method for evaluating the degree of discrimination accuracy with which a detection device, which is provided so as to be able to detect two gas substances, a first substance and a second substance, can detect the first substance and the second substance. The detection device is as described in the first embodiment, and includes a plurality of sensor elements. Here, an example will be described in which the number of sensor elements is s (s is an integer of 2 or more).

[0099] This evaluation method is a first step of adsorbing a first substance onto sensitive films of a plurality (s pieces) of sensor elements and measuring a characteristic value reflecting a change in a physical parameter, thereby obtaining multi-dimensional (s-dimensional) measurement data including information on the characteristic value; a second step of adsorbing a second substance onto the sensitive films of a plurality (s) of sensor elements and measuring a characteristic value reflecting a change in the physical parameter to obtain multi-dimensional (s-dimensional) measurement data including information on the characteristic value; A third step of performing a principal component analysis on the measurement data measured in the first step and the measurement data measured in the second step to calculate scores of two principal components; a fourth step of calculating, in a coordinate system having axes along the two principal components, a first probability ellipse that includes points having scores corresponding to a first material at a specific probability density, and a second probability ellipse that includes points having scores corresponding to a second material at the specific probability density; A fifth step of calculating a degree of separation D represented by the following formula (M1) from the first probability ellipse and the second probability ellipse; Includes.

[0100] D=L' / L (M1) (In formula (M1), L represents the distance between the center of the first density ellipse and the center of the second density ellipse, L' represents the distance between the point where the line segment connecting the center of the first probability ellipse and the center of the second probability ellipse intersects with the first probability ellipse and the point where the line segment intersects with the second probability ellipse.

[0101] Hereinafter, the evaluation method will be specifically described using the evaluation device 10 described in the first embodiment and taking as an example a case where a first principal component and a second principal component are adopted as the two principal components. In the first step, as shown in FIG. 1, a gas containing a first substance is supplied to the sensor elements 100A-100E to adsorb the first substance to the sensitive films 120A-120E. The characteristic values ​​reflecting the change in the physical parameters of the sensitive films 120A-120E caused by this adsorption are measured by the measuring units 110A-110E. Then, information on the measured characteristic values ​​is acquired through the output unit 300. Usually, the operation of adsorbing the first substance to the sensitive films 120A-120E and measuring the characteristic values ​​is performed multiple times. For example, the characteristic values ​​are measured N1 times (N1 is an integer of 2 or more) to acquire N1 pieces of five-dimensional measurement data obtained by adsorbing the first substance to the five sensitive films 120A-120E.

[0102] In the second step, a gas containing the second substance is supplied to the sensor elements 100A-100E to adsorb the second substance to the sensitive films 120A-120E. The characteristic values ​​reflecting the changes in the physical parameters of the sensitive films 120A-120E caused by this adsorption are measured by the measuring units 110A-110E. Then, information on the measured characteristic values ​​is obtained through the output unit 300. Usually, the operation of adsorbing the second substance to the sensitive films 120A-120E and measuring the characteristic values ​​is performed multiple times. For example, the characteristic values ​​are measured N2 times (N2 is an integer of 2 or more) to obtain N2 pieces of five-dimensional measurement data obtained by adsorbing the second substance to the five sensitive films 120A-120E. Here, N1 and N2 may be the same or different.

[0103] In the first and second steps, the information on the characteristic values ​​may be directly subjected to the principal component analysis as the measurement data, or the characteristic values ​​may be standardized as necessary and the obtained values ​​may be subjected to the principal component analysis as the measurement data. The standardization method is as described in the first embodiment.

[0104] In the third step, a principal component analysis is performed on the measurement data measured in the first step and the measurement data measured in the second step to calculate the scores of the two principal components. In this example, a first principal component score and a second principal component score are calculated. In detail, a principal component analysis is performed on N1 pieces of measurement data (measurement data acquired in the first step) including information on characteristic values ​​reflecting changes due to adsorption of the first substance, and N2 pieces of measurement data (measurement data acquired in the second step) including information on characteristic values ​​reflecting changes due to adsorption of the second substance. Through this principal component analysis, a first principal component score and a second principal component score for each of the N1 pieces of measurement data corresponding to the first substance, and a first principal component score and a second principal component score for each of the N2 pieces of measurement data corresponding to the second substance are calculated.

[0105] FIG. 4 shows a two-dimensional map in which a score pattern representing the first principal component score and the second principal component score calculated in the third step of the evaluation method according to the second embodiment of the present invention is displayed. In FIG. 4, a coordinate system with the first principal component (PC1) and the second principal component (PC2) as axes is adopted. The triangular points represent points having the first principal component score and the second principal component score corresponding to the first substance, and thus represent points including information on the characteristic value reflecting the change due to the adsorption of the first substance. The circular points represent points having the first principal component score and the second principal component score corresponding to the second substance, and thus represent points including information on the characteristic value reflecting the change due to the adsorption of the second substance. As shown in the two-dimensional map exemplified in FIG. 4, in general, due to the influence of fluctuations in the characteristic values ​​measured in the first and second steps, the coordinates of the triangular points corresponding to the first substance and the circular points corresponding to the secondary substances both vary.

[0106] In the fourth step, as shown in FIG. 4, a first probability ellipse E1 including points having a score corresponding to the first material at a specific probability density and a second probability ellipse E2 including points having a score corresponding to the second material at the specific probability density are calculated in a coordinate system with an axis of the principal component corresponding to the score calculated in the third step. Since the first principal component score and the second principal component score are adopted in this example, a first probability ellipse E1 including points having the first principal component score and the second principal component score corresponding to the first material (triangle points in FIG. 4) and a second probability ellipse E2 including points having the first principal component score and the second principal component score corresponding to the second material (circular points in FIG. 4) are calculated in a coordinate system with an axis of the first principal component (PC1) and the second principal component (PC2). A probability ellipse refers to an ellipse including points at a certain probability density. In the fourth step, the probability density of the first probability ellipse E1 and the probability density of the second probability ellipse E2 are set to be the same. A specific probability density can be set according to a required evaluation accuracy, for example, in a range of 80% to 99%. In the example shown in Fig. 4, the probability density is set to 95%. Therefore, in the example shown in Fig. 4, the first probability ellipse E1 includes N1 triangulation points corresponding to the first material with a probability density of 95%. The second probability ellipse E2 includes N2 circular points corresponding to the second material with a probability density of 95%.

[0107] In the fifth step, the degree of separation D, expressed by the formula (M1), is calculated from the first probability ellipse E1 and the second probability ellipse E2 calculated in the fourth step. D=L' / L (M1)

[0108] In formula (M1), L is the center O of the first probability ellipse E1. E1 and the center O of the second probability ellipse E2 E2 Therefore, L represents the distance between the center O of the first probability ellipse E1. E1 and the center O of the second probability ellipse E2 E2 A straight line segment S that connects L corresponds to the length of

[0109] In formula (M1), L' is the line segment S L Intersection point P where intersects with the first probability ellipse E1 E1 and the line segment SL Intersection point P where intersects with the second probability ellipse E2 E2 Therefore, L' represents the distance between the intersection point P E1 and intersection point P E2 Therefore, L' corresponds to the length of the straight line segment connecting the center O of the first probability ellipse E1 from the distance L. E1 From intersection point P E1 Distance L1 to the center O of the second probability ellipse E2 E2 From intersection point P E2 This corresponds to the distance L1 minus the distance L2 to the target point.

[0110] The larger the degree of separation D, the less likely the first probability ellipse E1 and the second probability ellipse E2 will overlap. Thus, the larger the degree of separation D, the greater the separation in the coordinate system between the range in which the triangular point corresponding to the first material is likely to be plotted and the range in which the circular point corresponding to the second material is likely to be plotted. Thus, the possibility of erroneously detecting the first material as the second material can be reduced, and the possibility of erroneously detecting the second material as the first material can be reduced. Therefore, the larger the degree of separation D, the higher the accuracy of identification of the detection by the detection device 10 can be evaluated.

[0111] In the second embodiment, an example was shown in which two types of gas substances, a first substance and a second substance, were detected, but in an actual detection device, there may be cases in which it is desired to detect three or more types of gas substances. In such a case, for example, the degree of separation D for a pair of two types of gas substances selected from the group of three or more types of gas substances is calculated using the above-mentioned evaluation method for all pairs that can be selected from the group of gas substances. Then, the average of the degrees of separation D for those pairs is calculated. If this average of the degrees of separation D is large, it can be evaluated that the identification accuracy of the group of three or more types of gas substances is high.

[0112] In this embodiment, an example is shown in which the first and second principal components are used as the two principal components, but the combination of the principal components is not limited to the above. For example, a combination of the first and third principal components may be used, or a combination of the second and third principal components may be used.

[0113] <Explanation of how to select the sensitive membrane> As described above, a detection device employing a sensitive film selected to satisfy the requirements (I) to (III) can detect a wide range of gas substances. In this case, from the viewpoint of obtaining a detection device capable of detecting each target substance belonging to a certain substance group with high accuracy, it is preferable to select a combination of sensitive films to be provided in the detection device so that the above-mentioned degree of separation D can be increased. For example, it is preferable to select a combination of sensitive films from among a plurality of candidate sensitive films having different compositions so that the degree of separation D between target substances belonging to the above-mentioned substance group can be increased. In addition, for example, when a new sensitive film is manufactured using a new polymer that has not been used as a material for a sensitive film, it is preferable to select a sensitive film to be combined with the new sensitive film so that the degree of separation D between target substances can be increased. A preferred embodiment of the method for selecting a sensitive film using the degree of separation D in this way will be described below. In the following description, a group of target substances to be detected using a detection device may be referred to as a "target substance group". In addition, a candidate sensitive film may be referred to as a "candidate sensitive film", and a sensitive film selected from the candidate sensitive films may be referred to as an "adopted sensitive film".

[0114] The method for selecting a sensitive film according to the third embodiment of the present invention is a method for selecting an adopted sensitive film for detecting each of target substances belonging to a target substance group from a plurality of candidate sensitive films having mutually different compositions. This selection method includes the following steps: providing the candidate sensitive film on a surface of a measurement section capable of measuring a characteristic value reflecting a change in a physical parameter caused by the adsorption of a target substance onto the candidate sensitive film, thereby obtaining a plurality of sensor elements; a step of adsorbing target substances belonging to a target substance group onto candidate sensitive films of a plurality of sensor elements and measuring characteristic values ​​thereof to obtain multi-dimensional measurement data including information on the characteristic values; performing a principal component analysis of the measurement data to calculate scores of two principal components; Calculating the degree of separation D between all two substances belonging to the target substance group from the scores; A step of selecting an adopted sensitive membrane from a plurality of candidate sensitive membranes based on a degree of separation D; Includes.

[0115] The details are as follows. The selection method according to this embodiment includes a step of providing a candidate sensitive film on the surface of a measurement unit to obtain a plurality of sensor elements. Here, an example will be described in which s candidate sensitive films are provided on s measurement units to obtain s sensor elements (s is an integer of 2 or more). The s sensor elements thus obtained are then provided on an element mounting section to prepare a detection device for the selection method. The detection device for the selection method may be the same as that described in the first embodiment, except that a candidate sensitive film is provided as a sensitive film on the measurement unit.

[0116] After the step of preparing the sensor element, the selection method according to this embodiment includes a step of adsorbing each of the target substances belonging to the target substance group onto the candidate sensitive films of the multiple sensor elements and measuring the characteristic values, thereby obtaining multi-dimensional measurement data including information on the characteristic values. In the example shown here, s sensor elements are used, so that s-dimensional measurement data is obtained for each target substance. Usually, the operation of adsorbing each target substance onto the candidate sensitive films and measuring the characteristic values ​​is performed multiple times (e.g., N3 times). As a result, multiple (N3) pieces of s-dimensional measurement data are obtained for each target substance. The step of obtaining the measurement data may include standardizing the characteristic values ​​as necessary.

[0117] After the step of obtaining the measurement data, the selection method according to the present embodiment includes a step of performing a principal component analysis of the measurement data to calculate the scores of two principal components. In this example, a case where a first principal component and a second principal component are adopted as the two principal components will be described as an example. The scores of the two principal components obtained by this principal component analysis (in this example, the first principal component score and the second principal component score) correspond to the coordinates of each point in a coordinate system with the two principal components as axes, as shown in FIG. 4. Therefore, for example, when the characteristic value of a certain target substance is measured N3 times, N3 points corresponding to the target substance are obtained in a two-dimensional map using the coordinate system.

[0118] After the step of performing the principal component analysis, the method for selecting a sensitive membrane according to this embodiment includes a step of calculating the degree of separation D between the target substances from the principal component scores. In this step, the degree of separation D is calculated between all two substances belonging to the target substance group. That is, for all pairs of two target substances that can be selected from the target substance group, the degree of separation D between the target substances in each pair is calculated.

[0119] The degree of separation D can be calculated by the method described in the second embodiment. That is, a first probability ellipse is calculated using one of the target substances belonging to the pair of two target substances as a first substance. This first probability ellipse represents an ellipse that includes points indicated by the principal component scores (in the example shown in this embodiment, the first principal component score and the second principal component score) corresponding to one of the target substances belonging to the pair at a specific probability density in a coordinate system with two principal components (in the example shown in this embodiment, the first principal component and the second principal component) as axes. Also, a second probability ellipse is calculated using the other target substance belonging to the pair as a second substance. This second probability ellipse represents an ellipse that includes points indicated by the principal component scores (in the example shown in this embodiment, the first principal component and the second principal component) corresponding to the other target substance belonging to the pair at the specific probability density in a coordinate system with two principal components (in the example shown in this embodiment, the first principal component and the second principal component) as axes. Then, the degree of separation D represented by the formula (M1) is calculated from the obtained first probability ellipse and second probability ellipse.

[0120] After the step of calculating the degree of separation D, the selection method according to this embodiment includes a step of selecting an adopted sensitive membrane based on the degree of separation D. As described above, the larger the degree of separation D, the higher the identification accuracy can be evaluated. Therefore, it is preferable to select an adopted sensitive membrane from the candidate sensitive membranes so as to obtain a large degree of separation D. For example, the adopted sensitive membrane may be selected so that the average of the calculated degrees of separation D is maximized. Also, for example, the adopted sensitive membrane may be selected so that the average of the calculated degrees of separation D is equal to or greater than a predetermined threshold. Furthermore, for example, the adopted sensitive membrane may be selected so that all of the calculated degrees of separation D are equal to or greater than a predetermined threshold.

[0121] According to the above-mentioned selection method of selecting the sensitive membrane to be adopted using the degree of separation D, it is possible to easily select a combination of sensitive membranes that can be expected to have high discrimination accuracy according to the target substance. Therefore, even when there are many types of target substances, many types of candidate sensitive membranes, or a new candidate sensitive membrane is used, it is possible to reduce the effort required to manufacture a detection device. Usually, due to cost and size constraints, there are limitations on the number of sensor elements that can be provided in one detection device, but by using the above-mentioned selection method, it is possible to manufacture a detection device that can obtain high discrimination accuracy even within such constraints with little effort.

[0122] In this embodiment, an example is shown in which the first and second principal components are used as the two principal components, but the combination of the principal components is not limited to the above. For example, a combination of the first and third principal components may be used, or a combination of the second and third principal components may be used.

[0123] <Sensor element set> The sensor element set according to the fourth embodiment of the present invention includes a plurality of sensor elements. These sensor elements are the same as those described in the first embodiment. Thus, the sensor elements included in the sensor element set according to this embodiment include sensitive films having different compositions. In particular, it is preferable that the polymers included in the sensitive films have different compositions. In addition, when a water adsorption test is performed in which water vapor is adsorbed on the sensitive films of the plurality of sensor elements to measure a characteristic value reflecting a change in a physical parameter, a coefficient of variation of the characteristic value that satisfies the above-mentioned requirement (I) is obtained. In addition, when an acetic acid adsorption test is performed in which acetic acid vapor is adsorbed on the sensitive films of the plurality of sensor elements to measure a characteristic value reflecting a change in a physical parameter, a coefficient of variation of the characteristic value that satisfies the above-mentioned requirement (II) is obtained. In addition, when a butylamine adsorption test is performed in which butylamine vapor is adsorbed on the sensitive films of the plurality of sensor elements to measure a characteristic value reflecting a change in a physical parameter, a coefficient of variation of the characteristic value that satisfies the above-mentioned requirement (III) is obtained. By using this sensor element set, it is possible to manufacture the detection device described in the first embodiment. The manufactured detection device includes the sensor element set according to this embodiment, and can obtain the advantages as described in the first embodiment.

[0124] <Sensitive membrane set> The sensitive membrane set according to the fifth embodiment of the present invention includes a plurality of sensitive membranes. These sensitive membranes are the same as those described in the first embodiment. Therefore, the sensitive membranes included in the sensitive membrane set according to this embodiment have different compositions. In particular, it is preferable that the polymers included in the sensitive membranes have different compositions. In addition, when a water adsorption test is performed in which the sensitive membranes of the plurality of sensor elements are adsorbed with water vapor to measure a characteristic value reflecting a change in physical parameters by providing the plurality of sensitive membranes on the surface of the measurement section, a coefficient of variation of the characteristic value that satisfies the above-mentioned requirement (I) is obtained. Furthermore, when a plurality of sensor elements are prepared by providing the plurality of sensitive membranes on the surface of the measurement section, and an acetic acid adsorption test is performed in which the sensitive membranes of the plurality of sensor elements are adsorbed with acetic acid vapor to measure a characteristic value reflecting a change in physical parameters by providing the plurality of sensitive membranes on the surface of the measurement section, a coefficient of variation of the characteristic value that satisfies the above-mentioned requirement (II) is obtained. Furthermore, when a plurality of sensor elements are prepared by providing the plurality of sensitive membranes on the surface of the measurement section, and a butylamine adsorption test is performed in which the sensitive membranes of the plurality of sensor elements are adsorbed with butylamine vapor to measure a characteristic value reflecting a change in physical parameters by providing the plurality of sensitive membranes on the surface of the measurement section, a coefficient of variation of the characteristic value that satisfies the above-mentioned requirement (III) is obtained. By using this sensitive membrane set, it is possible to manufacture the detection device described in the first embodiment. The manufactured detection device includes the sensitive membrane set according to this embodiment, and can obtain the advantages as described in the first embodiment.

[0125] <Polymer composition set> The polymer composition set according to the sixth embodiment of the present invention includes a plurality of polymer compositions. These polymer compositions are the same as those described in the first embodiment. Thus, the plurality of polymer compositions included in the polymer composition set according to this embodiment have different compositions. In particular, it is preferable that the non-volatile components (polymers, additives, etc.) of the plurality of polymer compositions have different compositions, and it is even more preferable that the polymers have different compositions. In addition, when a water adsorption test is performed in which a plurality of sensor elements are prepared by applying and drying the plurality of polymer compositions to the surface of the measurement section to form a sensitive film, and water vapor is adsorbed on the sensitive film of the plurality of sensor elements to measure a characteristic value reflecting a change in a physical parameter, a coefficient of variation of the characteristic value satisfying the above-mentioned requirement (I) is obtained. In addition, when a plurality of sensor elements are prepared by applying and drying the plurality of polymer compositions to the surface of the measurement section to form a sensitive film, and an acetic acid adsorption test is performed in which acetic acid vapor is adsorbed on the sensitive film of the plurality of sensor elements to measure a characteristic value reflecting a change in a physical parameter, a coefficient of variation of the characteristic value satisfying the above-mentioned requirement (II) is obtained. Furthermore, when a plurality of sensor elements are prepared by applying and drying the plurality of polymer compositions to the surface of the measurement part to form a sensitive film, and a butylamine adsorption test is performed in which butylamine vapor is adsorbed onto the sensitive film of the plurality of sensor elements to measure a characteristic value reflecting a change in a physical parameter, a coefficient of variation of the characteristic value that satisfies the above-mentioned requirement (III) is obtained. By using this polymer composition set, it is possible to manufacture the detection device described in the first embodiment. The manufactured detection device includes a sensitive film manufactured from the polymer composition set according to this embodiment, and can obtain the advantages described in the first embodiment.

[0126] <Applications of the detection device> The above-described detection device may be used to detect a target substance that can be adsorbed to the sensitive film. For example, the detection device is preferably used as a detection device for detecting an odor substance or a gas molecule.

[0127] The term "odor" includes a specific molecule or a group of different molecules each having their own concentration that can be obtained as olfactory information by humans or other living organisms, including humans.

[0128] In addition, the term "odor substance" broadly includes substances that can be adsorbed to a sensitive membrane. Therefore, substances that are not generally considered to be the cause of odors may also be included in the term "odor substance". An "odor" often contains multiple odor substances that cause it, and there may also be substances that are not recognized as odor substances or unknown odor substances. Hereinafter, even when simply referring to an "odor substance", it may not mean an individual odor substance, but rather a "collection of odor substances" that may contain multiple odor substances.

[0129] Furthermore, the term "gas molecule" includes any gaseous molecule. Therefore, the sensor element described above may be used to detect molecules that are not related to odor as a target substance. EXAMPLES

[0130] The present invention will be specifically described below with reference to examples. However, the present invention is not limited to the examples shown below. In the following description, "parts" and "%" representing amounts mean "parts by mass" and "% by mass", respectively, unless otherwise specified. Unless otherwise specified, the operations described below were carried out in air at room temperature and normal pressure (23° C., 1 atm).

[0131] <Production Example: Production of Polymer Composition> Polymer composition A was obtained by mixing 0.1 part of a polymer ("WED-S" manufactured by Soken Chemical Industries, Ltd.) and 10 parts of a solvent (N-methyl-2-pyrrolidone; NMP).

[0132] Polymer composition B was obtained by mixing 0.88 parts of polyvinyl acetate and 10 parts of a solvent (carbitol acetate).

[0133] Polymer composition C was obtained by mixing 0.2 parts of poly(styrene-acrylic acid) and 10 parts of a solvent (tetralin).

[0134] A polymer composition D was obtained by mixing 0.52 parts of poly(styrene-2-vinylpyridine) and 10 parts of a solvent (tetralin).

[0135] A polymer composition E was obtained by mixing 0.76 parts of poly(styrene-4-vinylpyridine) and 10 parts of a solvent (1,3-dimethyl-2-imidazolidinone).

[0136] Polymer composition F was obtained by mixing 0.66 parts of polysulfone and 10 parts of a solvent (methyl benzoate).

[0137] A polymer composition G was obtained by mixing 0.84 parts of polyacrylic acid and 10 parts of a solvent (1,3-dimethyl-2-imidazolidinone).

[0138] Polymer composition H was obtained by mixing 0.63 parts of phenol resin (DIC Corporation, "TD2090"), 0.63 parts of poly(styrene-acrylic acid), and 10 parts of a solvent (methyl benzoate).

[0139] Polymer composition I was obtained by mixing 0.29 parts of fluororesin (AGC Corporation's "Lumiflon LF200F"), 0.29 parts of phenoxy resin (Mitsubishi Chemical Corporation's "jer-1256"), and 10 parts of a solvent (carbitol acetate).

[0140] Polymer composition J was obtained by mixing 0.12 parts of polystyrene, 0.12 parts of a fluororesin ("Lumiflon LF200F" manufactured by AGC Corporation), and 10 parts of a solvent (methyl benzoate).

[0141] Polymer composition K was obtained by mixing 0.33 parts of butyral resin, 0.33 parts of fluororesin ("Lumiflon LF200F" manufactured by AGC Corporation), and 10 parts of a solvent (1-heptanol).

[0142] Polymer composition L was obtained by mixing 1.11 parts of a fluororesin (AGC Corporation's "Lumiflon LF200F"), 1.11 parts of a polyurethane resin, and 10 parts of a solvent (carbitol acetate).

[0143] Polymer composition M was obtained by mixing 0.15 parts of fluororesin (AGC Corporation's "Lumiflon LF200F"), 0.15 parts of modified cellulose, and 10 parts of a solvent (1,3-dimethyl-2-imidazolidinone).

[0144] Polymer composition N was obtained by mixing 0.3 parts of phenoxy resin ("jer-1256" manufactured by Mitsubishi Chemical Corporation), 0.3 parts of butyral resin, and 10 parts of a solvent (carbitol acetate).

[0145] A polymer composition O was obtained by mixing 0.63 parts of a phenol resin ("TD2090" manufactured by DIC Corporation), 0.63 parts of a polyimide resin, and 10 parts of a solvent (methyl benzoate).

[0146] A polymer composition P was obtained by mixing 0.09 part of polystyrene, 0.09 part of silicone resin, and 10 parts of a solvent (methyl benzoate).

[0147] A polymer composition Q was obtained by mixing 0.29 parts of a phenoxy resin ("jer-1256" manufactured by Mitsubishi Chemical Corporation), 0.29 parts of a silicone resin, and 10 parts of a solvent (1,3-dimethyl-2-imidazolidinone).

[0148] A polymer composition RR was obtained by mixing 0.11 part of ethyl cellulose, 0.11 part of polyurethane resin, and 10 parts of a solvent (1,3-dimethyl-2-imidazolidinone).

[0149] A polymer composition S was obtained by mixing 0.32 parts of butyral resin, 0.32 parts of polyimide resin, and 10 parts of a solvent (methyl benzoate).

[0150] Polymer composition T was obtained by mixing 0.27 parts of phenol resin (DIC Corporation, "TD2090"), 0.27 parts of polyvinyl acetate, and 10 parts of a solvent (methyl benzoate).

[0151] A polymer composition U was obtained by mixing 0.38 parts of silicone resin, 0.38 parts of polysulfone, and 10 parts of a solvent (methyl benzoate).

[0152] Polymer composition V was obtained by mixing 0.25 parts of polyimide, 0.25 parts of polysulfone, and 10 parts of a solvent (methyl benzoate).

[0153] A polymer composition W was obtained by mixing 0.31 part of poly(styrene-2-vinylpyridine), 0.31 part of poly4-vinylpyridine, and 10 parts of a solvent (γ-butyrolactone).

[0154] Polymer composition X was obtained by mixing 0.38 parts of phenoxy resin ("JER-1256" manufactured by Mitsubishi Chemical Corporation), 0.38 parts of polyvinylpyrrolidone, and 10 parts of a solvent (1,3-dimethyl-2-imidazolidinone).

[0155] A polymer composition Y was obtained by mixing 1.00 part of silicone resin, 0.04 parts of Tris(2,4-pentanedionato)aluminum(III), and 10 parts of a solvent (methyl benzoate).

[0156] A polymer composition Z was obtained by mixing 0.42 parts of poly(styrene-2-vinylpyridine), 0.42 parts of polyvinylpyrrolidone, and 10 parts of a solvent (γ-butyrolactone).

[0157] 0.87 parts of polyurethane resin, 0.87 parts of polyvinylpyrrolidone, and 10 parts of a solvent (heptanol) were mixed to obtain a polymer composition AA.

[0158] A polymer composition AB was obtained by mixing 0.95 parts of polyimide, 0.95 parts of polyvinylpyrrolidone, and 10 parts of a solvent (1,3-dimethyl-2-imidazolidinone).

[0159] A polymer composition AC was obtained by mixing 1.00 part of a phenoxy resin ("jer-1256" manufactured by Mitsubishi Chemical Corporation), 0.05 part of 18-Crown-6-Ether, and 10 parts of a solvent (carbitol acetate).

[0160] A polymer composition AD was obtained by mixing 0.75 parts of polystyrene, 0.05 parts of 18-Crown-6-Ether, and 10 parts of a solvent (carbitol acetate).

[0161] A polymer composition AE was obtained by mixing 0.35 parts of butyral resin, 0.05 parts of 18-Crown-6-Ether, and 10 parts of a solvent (carbitol acetate).

[0162] A polymer composition AF was obtained by mixing 1.5 parts of a phenolic resin (DIC Corporation, "TD2090"), 0.04 parts of Tris(2,4-pentanedionato)aluminum(III), and 10 parts of a solvent (carbitol acetate).

[0163] <Example 1> (1.1. Preparation of polymer composition set) From the polymer compositions produced above, polymer composition D, polymer composition H, polymer composition U, polymer composition AB and polymer composition AF were selected to prepare a polymer composition set.

[0164] (1.2. Manufacturing of sensor element sets) Each polymer composition included in the prepared polymer composition set was applied onto a piezoelectric element serving as a measuring unit (a piezoelectric element attached to the odor detection device "nose@MEMS" manufactured by I-PEX Corporation; the same applies below), and then dried to form a sensitive film. Specifically, polymer composition D was applied onto a piezoelectric element and dried to form a sensitive film D. Polymer composition H was applied onto another piezoelectric element and dried to form a sensitive film H. Polymer composition U was applied onto yet another piezoelectric element and dried to form a sensitive film U. Polymer composition AB was applied onto yet another piezoelectric element and dried to form a sensitive film AB. Polymer composition AF was applied onto yet another piezoelectric element and dried to form a sensitive film AF.

[0165] As a result of the above, a sensor element set was obtained including a sensor element D having a sensitive film D and a piezoelectric element, a sensor element H having a sensitive film H and a piezoelectric element, a sensor element U having a sensitive film U and a piezoelectric element, a sensor element AB having a sensitive film AB and a piezoelectric element, and a sensor element AF having a sensitive film AF and a piezoelectric element. This sensor element set includes the set of sensitive film D, sensitive film H, sensitive film U, sensitive film AB, and sensitive film AF.

[0166] (1.3. Water adsorption test) Sensor element D, sensor element H, sensor element U, sensor element AB, and sensor element AF were attached to an odor detection device (I-PEX "nose@MEMS").

[0167] 5 mL of liquid water was placed in the petri dish as the sample material, and the dish was covered with a petri dish cover. A pump (I-PEX) was connected to the petri dish cover via a tube, and the pump was connected to the odor detection device via a tube. The pump was turned on for 5 seconds, and the sample material (water vapor) that had volatilized in the headspace gas of the petri dish was sprayed onto the sensitive film of the sensor element. The pump was then turned off for 55 seconds. During this total of 60 seconds, the output value converted from the vibration frequency of the piezoelectric element was measured. Specifically, the output value was measured by subtracting a predetermined reference value from the vibration frequency (same below).

[0168] The 60-second measurement operation counted as one measurement, and 30 measurements were performed. In each measurement, the output value changed over time, so the magnitude of change was calculated by subtracting the initial value (output value at 0 seconds) from the extreme value (peak top output value) of the output value in the period from 0 seconds to 10 seconds. The average value of the magnitude of change for the total of 30 measurements was calculated, and the characteristic value (amount of change in output value) of each sensor element was obtained for calculating the coefficient of variation. The obtained characteristic value had a value that reflected the change in vibration frequency as a physical parameter.

[0169] The coefficient of variation was calculated from the five characteristic values ​​obtained using sensor element D, sensor element H, sensor element U, sensor element AB, and sensor element AF. Specifically, the average value and standard deviation were calculated from the five characteristic values, and the standard deviation was divided by the average value to calculate the coefficient of variation.

[0170] (1.4. Acetic acid adsorption test) Except for using 5 mL of acetic acid instead of water, the same method as in the water adsorption test described above was used to measure the characteristic value (change in output value) reflecting the change in vibration frequency due to the adsorption of the sample substance (acetic acid vapor) onto sensitive films D, H, U, AB, and AF, and the coefficient of variation was calculated.

[0171] (1.5. Butylamine adsorption test) Except for using 5 mL of butylamine instead of water, the same method as in the water adsorption test described above was used to measure the characteristic value (change in output value) reflecting the change in vibration frequency due to the adsorption of the sample substance (butylamine vapor) onto sensitive films D, H, U, AB, and AF, and calculate the coefficient of variation.

[0172] (1.6. Measurement of Separation Degree) A detection test for water as a sample substance was carried out using an odor detection device (I-PEX Corporation's "nose@MEMS") equipped with the above-mentioned sensor element D, sensor element H, sensor element U, sensor element AB, and sensor element AF. Specifically, 5 mL of liquid water was placed in the petri dish as the sample material, and the petri dish was covered with a petri dish cover. A pump (manufactured by I-PEX) was connected to the petri dish cover via a tube, and the pump and the odor detection device were connected via a tube. The pump was operated for 5 seconds, and the sample material (water vapor) volatilized in the headspace gas of the petri dish was sprayed onto the sensitive film of the sensor element. The pump was then stopped for 55 seconds. During this total of 60 seconds, the output value converted from the vibration frequency of the piezoelectric element was measured. The measurement operation for the above 60 seconds was counted as one measurement, and 30 measurements were performed. In the above measurement, the initial value (output value at 0 seconds) was subtracted from the extreme value (peak top output value) of the output value from 0 seconds to 10 seconds to determine the magnitude of the change in the output value due to the adsorption of water, and a total of 30 characteristic values ​​(changes in the output value) were obtained.

[0173] In the above measurement operation, 30 pieces of measurement data of the characteristic values ​​due to water adsorption were obtained. The above 30 pieces of measurement data were five-dimensional data including five characteristic values ​​of the sensor elements, namely, sensor element D, sensor element H, sensor element U, sensor element AB, and sensor element AF.

[0174] Thirty pieces of measurement data including five-dimensional characteristic values ​​due to the adsorption of propanol were measured in the same manner as in the water detection test described above, except that propanol was used instead of water as the sample material.

[0175] Thirty pieces of measurement data including five-dimensional characteristic values ​​due to the adsorption of hexanol were measured using the same method as in the water detection test described above, except that hexanol was used instead of water as the sample material.

[0176] Thirty pieces of measurement data including five-dimensional characteristic values ​​due to the adsorption of octanol were measured in the same manner as in the water detection test described above, except that octanol was used instead of water as the sample material.

[0177] The measurement data of the above characteristic values ​​was subjected to principal component analysis using the data analysis function of "nose@MEMS Viewer" manufactured by I-PEX, and the first principal component score and the second principal component score were calculated. The score patterns of the obtained first principal component score and second principal component score are shown in Figure 5. In Figure 5, the score pattern showing the measurement data is displayed on a two-dimensional map using a coordinate system with the first principal component (PC1) and the second principal component (PC2) as axes.

[0178] In the coordinate system shown in Figure 5, we calculated probability ellipses that contain the measurement data corresponding to each sample material with a probability density of 95%. These probability ellipses are shown by dashed lines in Figure 5. From these probability ellipses, we calculated the degree of separation D between the sample materials. Specifically, we performed the following calculations.

[0179] A method for calculating the degree of separation D between water and propanol will be described. A straight line segment connecting the center of the probability ellipse corresponding to water (first probability ellipse) and the center of the probability ellipse corresponding to propanol (second probability ellipse) was calculated. The intersection point between the line segment and the probability ellipse corresponding to water was calculated. The intersection point between the line segment and the probability ellipse corresponding to propanol was calculated. Then, the degree of separation D was calculated from the distance L between the centers of the two probability ellipses and the distance L' between the two intersection points according to the following formula (M1). D=L' / L (M1)

[0180] Using the same calculation method, the resolution between water and hexanol, the resolution between water and octanol, the resolution between propanol and hexanol, the resolution between propanol and octanol, and the resolution between hexanol and octanol were calculated. The average of these six resolutions was then calculated. The larger the average resolution, the higher the discrimination accuracy of the sample material (in this embodiment, water, propanol, hexanol, and octanol) can be detected.

[0181] (1.7. Results of Example 1) The results of Example 1 are shown in Table 1 below.

[0182] [Table 1]

[0183] <Example 2> Except for using polymer compositions D, H, Y, AB, and AF instead of polymer compositions D, H, U, AB, and AF as the polymer composition set, the polymer composition set was manufactured, the sensor element set was manufactured, a water adsorption test, an acetic acid adsorption test, a butylamine adsorption test, and the measurement of the degree of separation were performed in the same manner as in Example 1. The score patterns of the first principal component score and the second principal component score obtained by performing the principal component analysis in the measurement of the degree of separation in Example 2 are shown in FIG. 6. The results of Example 2 are shown in Table 2 below.

[0184] [Table 2]

[0185] <Example 3> As the polymer composition set, polymer compositions D, Q, Y, AB and AF were adopted instead of polymer compositions D, H, U, AB and AF. In addition, water, propionaldehyde, hexanal and octanal were used instead of water, propanol, hexanol and octanol as sample substances to be used for measuring the degree of separation. Except for the above, the same method as in Example 1 was used to manufacture the polymer composition set, manufacture the sensor element set, perform a water adsorption test, an acetic acid adsorption test, a butylamine adsorption test, and measure the degree of separation. The score patterns of the first principal component score and the second principal component score obtained by performing principal component analysis in the measurement of the degree of separation in Example 3 are shown in FIG. 7. The results of Example 3 are shown in Table 3 below.

[0186] [Table 3]

[0187] <Example 4> As the polymer composition set, polymer compositions D, H, Y, AB, and AF were used instead of polymer compositions D, H, U, AB, and AF. In addition, instead of water, propanol, hexanol, and octanol, water, methyl acetate, butyl acetate, and hexyl acetate were used as sample substances for measuring the degree of separation. Except for the above, the same method as in Example 1 was used to manufacture the polymer composition set, manufacture the sensor element set, perform the water adsorption test, the acetic acid adsorption test, the butylamine adsorption test, and measure the degree of separation. The score patterns of the first principal component score and the second principal component score obtained by performing the principal component analysis in the measurement of the degree of separation in Example 4 are shown in FIG. 8. In FIG. 8, "methyl ac" represents methyl acetate, "butyl ac" represents butyl acetate, and "hexyl ac" represents hexyl acetate. The results of Example 4 are shown in Table 4 below.

[0188] [Table 4]

[0189] <Example 5> The polymer composition set was manufactured, the sensor element set was manufactured, a water adsorption test, an acetic acid adsorption test, a butylamine adsorption test, and the separation degree was measured in the same manner as in Example 1, except that water, propanol, hexanol, and octanol were used as the sample substances for the separation degree measurement, instead of water, propanol, hexanol, and octanol. The score patterns of the first principal component score and the second principal component score obtained by performing the principal component analysis in the separation degree measurement in Example 5 are shown in FIG. 9. In FIG. 9, "methyl ac" represents methyl acetate. The results of Example 5 are shown in Table 5 below.

[0190] [Table 5]

[0191] <Example 6> As the polymer composition set, polymer compositions D, H, Y, AB, and AF were used instead of polymer compositions D, H, U, AB, and AF. In addition, water, propanol, propionaldehyde, and methyl acetate were used instead of water, propanol, hexanol, and octanol as sample substances to be used for measuring the degree of separation. Except for the above, the same method as in Example 1 was used to manufacture the polymer composition set, manufacture the sensor element set, perform a water adsorption test, an acetic acid adsorption test, a butylamine adsorption test, and measure the degree of separation. The score patterns of the first principal component score and the second principal component score obtained by performing principal component analysis in the measurement of the degree of separation in Example 6 are shown in FIG. 10. In FIG. 10, "methyl ac" represents methyl acetate. The results of Example 6 are shown in Table 6 below.

[0192] [Table 6]

[0193] <Comparative Example 1> The polymer composition set was manufactured, the sensor element set was manufactured, a water adsorption test, an acetic acid adsorption test, a butylamine adsorption test, and a measurement of the degree of separation were performed in the same manner as in Example 1, except that the polymer compositions AE, I, H, O, and V were used instead of the polymer compositions D, H, U, AB, and AF as the polymer composition set. The score patterns of the first principal component score and the second principal component score obtained by performing the principal component analysis in the measurement of the degree of separation in Comparative Example 1 are shown in FIG. 11. The results of Comparative Example 1 are shown in Table 7 below.

[0194] [Table 7]

[0195] <Comparative Example 2> As the polymer composition set, polymer compositions Z, W, X, A and G were adopted instead of polymer compositions D, H, U, AB and AF. In addition, water, propionaldehyde, hexanal and octanal were used instead of water, propanol, hexanol and octanol as sample substances to be used for measuring the degree of separation. Except for the above, the same method as in Example 1 was used to manufacture the polymer composition set, manufacture the sensor element set, perform a water adsorption test, an acetic acid adsorption test, a butylamine adsorption test, and measure the degree of separation. The score patterns of the first principal component score and the second principal component score obtained by performing principal component analysis in the measurement of the degree of separation in Comparative Example 2 are shown in FIG. 12. The results of Comparative Example 2 are shown in Table 8 below.

[0196] [Table 8]

[0197] <Comparative Example 3> As the polymer composition set, polymer compositions Z, W, X, A and G were used instead of polymer compositions D, H, U, AB and AF. In addition, instead of water, propanol, hexanol and octanol, water, methyl acetate, butyl acetate and hexyl acetate were used as sample substances for measuring the degree of separation. Except for the above, the same method as in Example 1 was used to manufacture the polymer composition set, manufacture the sensor element set, perform the water adsorption test, the acetic acid adsorption test, the butylamine adsorption test and measure the degree of separation. The score patterns of the first principal component score and the second principal component score obtained by performing the principal component analysis in the measurement of the degree of separation in Comparative Example 3 are shown in FIG. 13. In FIG. 13, "methyl ac" represents methyl acetate, "butyl ac" represents butyl acetate and "hexyl ac" represents hexyl acetate. The results of Comparative Example 3 are shown in Table 9 below.

[0198] [Table 9]

[0199] <Comparative Example 4> As the polymer composition set, polymer compositions AE, I, H, O and V were used instead of polymer compositions D, H, U, AB and AF. In addition, water, propanol, propionaldehyde and methyl acetate were used instead of water, propanol, hexanol and octanol as sample substances to be used for measuring the degree of separation. Except for the above, the same method as in Example 1 was used to manufacture the polymer composition set, manufacture the sensor element set, perform the water adsorption test, the acetic acid adsorption test, the butylamine adsorption test and measure the degree of separation. The score patterns of the first principal component score and the second principal component score obtained by performing the principal component analysis in the measurement of the degree of separation in Comparative Example 4 are shown in FIG. 14. In FIG. 14, "methyl ac" represents methyl acetate. The results of Comparative Example 4 are shown in Table 10 below.

[0200] [Table 10]

[0201] <Comparative Example 5> The polymer composition set was manufactured, the sensor element set was manufactured, a water adsorption test, an acetic acid adsorption test, a butylamine adsorption test, and a measurement of the degree of separation were performed in the same manner as in Example 1, except that polymer compositions J, B, K, AE, and X were used instead of polymer compositions D, H, U, AB, and AF as the polymer composition set. The score patterns of the first principal component score and the second principal component score obtained by performing principal component analysis in the measurement of the degree of separation in Comparative Example 5 are shown in FIG. 15. The results of Comparative Example 5 are shown in Table 11 below.

[0202] [Table 11]

[0203] <Comparative Example 6> As the polymer composition set, polymer compositions P, N, K, AE and X were adopted instead of polymer compositions D, H, U, AB and AF. In addition, water, propionaldehyde, hexanal and octanal were used instead of water, propanol, hexanol and octanol as sample substances to be used for measuring the degree of separation. Except for the above, the same method as in Example 1 was used to manufacture the polymer composition set, manufacture the sensor element set, perform a water adsorption test, an acetic acid adsorption test, a butylamine adsorption test and measure the degree of separation. The score patterns of the first principal component score and the second principal component score obtained by performing principal component analysis in the measurement of the degree of separation in Comparative Example 6 are shown in FIG. 16. The results of Comparative Example 6 are shown in Table 12 below.

[0204] [Table 12]

[0205] <Comparative Example 7> As the polymer composition set, polymer compositions RR, B, M, AE and X were adopted instead of polymer compositions D, H, U, AB and AF. In addition, instead of water, propanol, hexanol and octanol, water, methyl acetate, butyl acetate and hexyl acetate were used as sample substances for measuring the degree of separation. Except for the above, the same method as in Example 1 was used to manufacture the polymer composition set, manufacture the sensor element set, perform the water adsorption test, the acetic acid adsorption test, the butylamine adsorption test and measure the degree of separation. The score patterns of the first principal component score and the second principal component score obtained by performing the principal component analysis in the measurement of the degree of separation in Comparative Example 7 are shown in FIG. 17. In FIG. 17, "methyl ac" represents methyl acetate, "butyl ac" represents butyl acetate and "hexyl ac" represents hexyl acetate. The results of Comparative Example 7 are shown in Table 13 below.

[0206] [Table 13]

[0207] <Comparative Example 8> As the polymer composition set, polymer compositions J, B, K, AE and X were adopted instead of polymer compositions D, H, U, AB and AF. In addition, instead of water, propanol, hexanol and octanol, water, propanol, propionaldehyde and methyl acetate were used as sample substances to be subjected to the measurement of the degree of separation. Except for the above, the same method as in Example 1 was used to manufacture the polymer composition set, manufacture the sensor element set, perform the water adsorption test, the acetic acid adsorption test, the butylamine adsorption test and measure the degree of separation. The score patterns of the first principal component score and the second principal component score obtained by performing the principal component analysis in the measurement of the degree of separation in Comparative Example 8 are shown in FIG. 18. In FIG. 18, "methyl ac" represents methyl acetate. The results of Comparative Example 8 are shown in Table 14 below.

[0208] [Table 14]

[0209] <Comparative Example 9> The polymer composition set was manufactured, the sensor element set was manufactured, a water adsorption test, an acetic acid adsorption test, a butylamine adsorption test, and a measurement of the degree of separation were performed in the same manner as in Example 1, except that the polymer compositions U, AC, N, AA, and T were used instead of the polymer compositions D, H, U, AB, and AF as the polymer composition set. The score patterns of the first principal component score and the second principal component score obtained by performing the principal component analysis in the measurement of the degree of separation in Comparative Example 9 are shown in FIG. 19. The results of Comparative Example 9 are shown in Table 15 below.

[0210] [Table 15]

[0211] <Comparative Example 10> As the polymer composition set, polymer compositions U, S, N, AA and L were adopted instead of polymer compositions D, H, U, AB and AF. In addition, water, propionaldehyde, hexanal and octanal were used instead of water, propanol, hexanol and octanol as sample substances to be used for measuring the degree of separation. Except for the above, the same method as in Example 1 was used to manufacture the polymer composition set, manufacture the sensor element set, perform a water adsorption test, an acetic acid adsorption test, a butylamine adsorption test and measure the degree of separation. The score patterns of the first principal component score and the second principal component score obtained by performing principal component analysis in the measurement of the degree of separation in Comparative Example 10 are shown in FIG. 20. The results of Comparative Example 10 are shown in Table 16 below.

[0212] [Table 16]

[0213] <Comparative Example 11> As the polymer composition set, polymer compositions U, I, S, AA and T were used instead of polymer compositions D, H, U, AB and AF. In addition, instead of water, propanol, hexanol and octanol, water, methyl acetate, butyl acetate and hexyl acetate were used as sample substances for measuring the degree of separation. Except for the above, the same method as in Example 1 was used to manufacture the polymer composition set, manufacture the sensor element set, perform the water adsorption test, the acetic acid adsorption test, the butylamine adsorption test and measure the degree of separation. The score patterns of the first principal component score and the second principal component score obtained by performing the principal component analysis in the measurement of the degree of separation in Comparative Example 11 are shown in FIG. 21. In FIG. 21, "methyl ac" represents methyl acetate, "butyl ac" represents butyl acetate and "hexyl ac" represents hexyl acetate. The results of Comparative Example 11 are shown in Table 17 below.

[0214] [Table 17]

[0215] <Comparative Example 12> As the polymer composition set, polymer compositions E, AD, F, C and G were used instead of polymer compositions D, H, U, AB and AF. In addition, water, propanol, propionaldehyde and methyl acetate were used instead of water, propanol, hexanol and octanol as sample substances to be used for measuring the degree of separation. Except for the above, the same method as in Example 1 was used to manufacture the polymer composition set, manufacture the sensor element set, perform the water adsorption test, the acetic acid adsorption test, the butylamine adsorption test and measure the degree of separation. The score patterns of the first principal component score and the second principal component score obtained by performing the principal component analysis in the measurement of the degree of separation in Comparative Example 12 are shown in FIG. 22. In FIG. 22, "metyl ac" stands for methyl acetate. The results of Comparative Example 12 are shown in Table 18 below.

[0216] [Table 18]

[0217] <Consideration> In the examples in which the coefficients of variation obtained in the water adsorption test, acetic acid adsorption test, and butylamine adsorption test satisfy the above-mentioned requirements, in order to confirm that a higher discrimination accuracy can be obtained than in the comparative examples, the results of the above-mentioned examples and comparative examples are summarized for each sample substance.

[0218] First, the results of Examples 1 and 2 and Comparative Examples 1, 5, and 9, in which water, propanol, hexanol, and octanol were detected as sample substances, are summarized in Table 19 below. In these Examples and Comparative Examples, it is verified whether alcohols with different carbon numbers can be identified and detected. As shown in Table 19, Examples 1 and 2 have a higher average degree of separation than Comparative Examples 1, 5, and 9, and it can be seen that the identification accuracy has been improved.

[0219] [Table 19]

[0220] Next, the results of Example 3 and Comparative Examples 2, 6, and 10, in which water, propionaldehyde, hexanal, and octanal were detected as sample substances, are summarized in Table 20 below. In these Examples and Comparative Examples, it is verified whether aldehydes with different carbon numbers can be identified and detected. As shown in Table 20, Example 3 has a higher average separation degree than Comparative Examples 2, 6, and 10, and it can be seen that the identification accuracy has been improved.

[0221] [Table 20]

[0222] Next, the results of Example 4 and Comparative Examples 3, 7, and 11, in which water, methyl acetate, butyl acetate, and hexyl acetate were detected as sample substances, are summarized in Table 21 below. In these Examples and Comparative Examples, it is verified whether esters with different carbon numbers can be identified and detected. As shown in Table 21, Example 4 has a higher average separation degree than Comparative Examples 3, 7, and 11, and it can be seen that the identification accuracy has been improved.

[0223] [Table 21]

[0224] Next, the results of Examples 5 and 6 and Comparative Examples 4, 8, and 12, in which water, propanol, propionaldehyde, and methyl acetate were detected as sample substances, are summarized in Table 22 below. In these Examples and Comparative Examples, it is verified whether compounds having different functional groups (specifically, alcohols, aldehydes, and esters) can be identified and detected. As shown in Table 22, Examples 5 and 6 have a higher average degree of separation than Comparative Examples 4, 8, and 12, and it can be seen that the identification accuracy has been improved.

[0225] [Table 22]

[0226] From the above results, it can be seen that according to the present invention, it is possible to improve the discrimination accuracy in a detection method for detecting a wide range of sample materials. [Explanation of symbols]

[0227] 10. Detection Device 100A~100E Sensor element 110A~110E Measuring part 120A~120E Sensitive membrane 200 Element mounting part 210 Aperture 300 Output section E1 First density ellipse E2 Second Density Ellipse O E1 Center of the first probability ellipse O E2 Center of the second probability ellipse S L Center O of the first probability ellipse E1 and the center of the second probability ellipse, O E2 A line segment connecting P E1 First probability ellipse E1 and line segment S L Intersection with P E2 The second probability ellipse E2 and the line segment S L Intersection with

Claims

1. A detection device comprising a plurality of sensor elements; Each of the plurality of sensor elements includes a sensitive film containing one or more polymers, and a measurement unit having the sensitive film on a surface thereof and capable of measuring a characteristic value reflecting a change in a physical parameter caused by the adsorption of a substance to the sensitive film; The sensitive films of the plurality of sensor elements have different compositions; When a water adsorption test is performed in which water vapor is adsorbed on the sensitive films of a plurality of sensor elements to measure characteristic values, the coefficient of variation of the characteristic values ​​is 0.2 or more; When an acetic acid adsorption test is performed in which acetic acid vapor is adsorbed on the sensitive films of a plurality of sensor elements to measure a characteristic value, the coefficient of variation of the characteristic value is 0.5 or more; A detection device, in which, when a butylamine adsorption test is carried out in which butylamine vapor is adsorbed onto sensitive films of a plurality of sensor elements to measure characteristic values, the coefficient of variation of the characteristic values ​​is 1.5 or more.

2. 2. The detection device according to claim 1, wherein the sensitive films of the plurality of sensor elements include two or more polymers selected from the group consisting of a ring-containing polymer, a hydrocarbon-based polymer, a fluorine-based polymer, and a silicone-based polymer.

3. 2. The detection device according to claim 1, wherein at least one of the sensitive films of the plurality of sensor elements comprises two or more selected from the group consisting of a ring-structure-containing polymer, a hydrocarbon-based polymer, a fluorine-based polymer, and a silicone-based polymer.

4. The detection device according to claim 1 , wherein the measurement portion comprises a piezoelectric element.

5. A sensor element set including a plurality of sensor elements each including a sensitive film containing one or more polymers, and a measurement unit having the sensitive film on a surface thereof and capable of measuring a characteristic value reflecting a change in a physical parameter caused by adsorption of a substance to the sensitive film, comprising: The sensitive films of the plurality of sensor elements have different compositions; When a water adsorption test is performed in which water vapor is adsorbed on the sensitive films of a plurality of sensor elements to measure characteristic values, the coefficient of variation of the characteristic values ​​is 0.2 or more; When an acetic acid adsorption test is performed in which acetic acid vapor is adsorbed on the sensitive films of a plurality of sensor elements to measure a characteristic value, the coefficient of variation of the characteristic value is 0.5 or more; A sensor element set, in which, when a butylamine adsorption test is conducted in which butylamine vapor is adsorbed onto sensitive films of a plurality of sensor elements to measure characteristic values, the coefficient of variation of the characteristic values ​​is 1.5 or more.

6. A sensitive membrane set including a plurality of sensitive membranes including one or more polymers; The multiple sensitive films have different compositions; a plurality of sensor elements are prepared by providing each sensitive film on the surface of a measurement part capable of measuring a characteristic value reflecting a change in a physical parameter caused by the adsorption of a substance onto the sensitive film, and when a water adsorption test is performed in which water vapor is adsorbed onto the sensitive films of the plurality of sensor elements to measure the characteristic value, the coefficient of variation of the characteristic value is 0.2 or more; When an acetic acid adsorption test is performed in which acetic acid vapor is adsorbed on the sensitive films of the plurality of sensor elements to measure a characteristic value, the coefficient of variation of the characteristic value is 0.5 or more; A sensitive membrane set, in which, when a butylamine adsorption test is conducted in which butylamine vapor is adsorbed onto the sensitive membranes of the plurality of sensor elements to measure a characteristic value, the coefficient of variation of the characteristic value is 1.5 or more.

7. A polymer composition set comprising a plurality of polymer compositions comprising one or more polymers and a solvent; The plurality of polymer compositions have different compositions from one another; a plurality of sensor elements are prepared, the sensor elements comprising a sensitive film formed by applying and drying a polymer composition, and a measurement unit having the sensitive film on its surface and capable of measuring a characteristic value reflecting a change in a physical parameter caused by the adsorption of a substance onto the sensitive film; and when a water adsorption test is performed in which water vapor is adsorbed onto the sensitive films of the plurality of sensor elements and the characteristic values ​​are measured, the coefficient of variation of the characteristic value is 0.2 or more; When an acetic acid adsorption test is performed in which acetic acid vapor is adsorbed on the sensitive films of the plurality of sensor elements to measure a characteristic value, the coefficient of variation of the characteristic value is 0.5 or more; A polymer composition set, wherein when a butylamine adsorption test is conducted in which butylamine vapor is adsorbed onto the sensitive films of the plurality of sensor elements to measure a characteristic value, the coefficient of variation of the characteristic value is 1.5 or more.

8. A method for evaluating a detection device having a plurality of sensor elements, comprising: Each of the plurality of sensor elements includes a sensitive film and a measurement unit having the sensitive film on a surface thereof and capable of measuring a characteristic value reflecting a change in a physical parameter caused by the adsorption of a substance to the sensitive film; a first step of causing a first substance to be adsorbed on the sensitive films of a plurality of sensor elements and measuring characteristic values ​​to obtain multi-dimensional measurement data including information on the characteristic values; a second step of causing a second substance to be adsorbed on the sensitive films of the plurality of sensor elements to measure characteristic values, thereby obtaining multi-dimensional measurement data including information on the characteristic values; A third step of performing a principal component analysis on the measurement data measured in the first step and the measurement data measured in the second step to calculate scores of two principal components; a fourth step of calculating, in a coordinate system having axes of the two principal components, a first probability ellipse including points having a score corresponding to a first material at a specific probability density, and a second probability ellipse including points having a score corresponding to a second material at the specific probability density; A fifth step of calculating a degree of separation D represented by the following formula (M1) from the first probability ellipse and the second probability ellipse; (c) evaluation methods; D = L' / L (M1) (In formula (M1), L represents the distance between the center of the first probability ellipse and the center of the second probability ellipse; L' represents the distance between the point where the line segment connecting the center of the first probability ellipse and the center of the second probability ellipse intersects with the first probability ellipse and the point where the line segment intersects with the second probability ellipse.

9. A method for selecting a sensitive film for detecting each of substances belonging to a substance group from a plurality of sensitive film candidates having different compositions; The selection method is providing a candidate sensitive film on a surface of a measurement unit capable of measuring a characteristic value reflecting a change in a physical parameter caused by the adsorption of a substance onto the candidate sensitive film to obtain a plurality of sensor elements; a step of adsorbing a substance belonging to a substance group onto the candidate sensitive films of a plurality of sensor elements and measuring characteristic values ​​thereof to obtain multi-dimensional measurement data including information on the characteristic values; performing a principal component analysis of the measurement data to calculate scores of two principal components; Calculating the degree of separation D between every two substances belonging to the substance group from the scores; selecting a sensitive membrane from a plurality of sensitive membrane candidates based on the degree of separation D; The calculation method of the degree of separation D is as follows: calculating a first probability ellipse including points indicated by scores corresponding to one of the two substances at a specific probability density in a coordinate system having axes of the two principal components, and a second probability ellipse including points indicated by scores corresponding to the other of the two substances at the specific probability density; A selection method comprising: a step of calculating a degree of separation D, expressed by the following formula (M1), from the first probability ellipse and the second probability ellipse. D = L' / L (M1) (In formula (M1), L represents the distance between the center of the first probability ellipse and the center of the second probability ellipse; L' represents the distance between the point where the line segment connecting the center of the first probability ellipse and the center of the second probability ellipse intersects with the first probability ellipse and the point where the line segment intersects with the second probability ellipse.

Images