Permeability evaluation method for fluid, evaluation device for permeability of fluid, porous material, and electrochemical cell

Abstract

To provide a permeability evaluation method for a fluid, etc., for evaluating permeability of a fluid with respect to a porous material based on an orientation of fibers constituting the porous material.SOLUTION: Disclosed is a permeability evaluation method for a fluid with respect to a porous material formed from a plurality of fibers. The permeability evaluation method for the fluid includes: an imaging data acquisition step of acquiring imaging data in which the plurality of fibers of the porous material is imaged; a form information generation step of generating form information including at least a part of contours of the fibers which are imaged in the imaging data; a detection step of detecting angles formed by the fibers, which are imaged in the imaging data, with respect to a reference direction on the basis of the form information; and an evaluation step of evaluating permeability of the fluid in accordance with a distribution mode of the angles of the fibers.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a method for evaluating fluid permeability through a porous material formed of a plurality of fibers, an apparatus for evaluating fluid permeability, a porous material, and an electrochemical cell. [Background technology]

[0002] A fuel cell is a device that utilizes the oxidation-reduction reaction of water. A water electrolysis device is also a device that utilizes the oxidation-reduction reaction of water, and is in a reverse reaction relationship with a fuel cell. For this reason, the two devices are constructed using many common parts. Hereinafter, fuel cells and water electrolysis devices will also be referred to as fuel cells, etc.

[0003] A polymer electrolyte fuel cell, which is an example of a fuel cell, includes a membrane electrode assembly in which electrodes containing a catalyst are bonded to both sides of an electrolyte membrane, gas diffusion layers disposed on each side of the membrane electrode assembly, and separators disposed on the outside of each of the gas diffusion layers.

[0004] A polymer electrolyte water electrolysis cell and an anion exchange membrane water electrolysis cell, which are examples of fuel cells, have a membrane electrode assembly in which catalyst-containing electrodes are bonded to both sides of an electrolyte membrane, porous transport layers disposed on both sides of the membrane electrode assembly, and separators disposed on the outer sides of the porous transport layers. Hereinafter, the gas diffusion layers and porous transport layers are also referred to as diffusion layers.

[0005] The gas diffusion layer is made of a porous material formed of a plurality of fibers. For example, Patent Document 1 discloses a gas diffusion layer including a porous substrate made of a conductive material, a first coating containing M-Ti oxide formed on one surface of the substrate, and a second coating containing a conductive noble metal oxide or the like formed on the other surface of the substrate.

[0006] In a vehicle equipped with a fuel cell, the gas diffusion layer is continuously subjected to forces caused by acceleration and deceleration of the vehicle. When stress is continuously applied to the gas diffusion layer, the pores of the gas diffusion layer become smaller, which is called creep. When creep occurs, gas diffusion in the gas diffusion layer may be hindered.

[0007] The gas diffusion resistance of the gas diffusion layer when such creep occurs is calculated. For example, Patent Document 2 discloses a fuel cell that includes a memory unit that stores the correspondence between the gas diffusion resistance of the gas diffusion layer and the creep amount of the gas diffusion layer, and a diffusion resistance acquisition unit that grasps the increase status of the gas diffusion resistance based on the creep amount corresponding to one gas diffusion resistance. [Prior art documents] [Patent documents]

[0008] [Patent Document 1] Japanese Patent Application Publication No. 2023-076968 [Patent Document 2] Japanese Patent Application Laid-Open No. 2012-221609 Summary of the Invention [Problem to be solved by the invention]

[0009] For example, a porous material is formed into a sheet, and then the sheet is cut to a predetermined size for use as a diffusion layer. Even when diffusion layers cut from the same molded body are used in fuel cells, etc., variations in performance of the fuel cells, etc. may be observed. The cause of such variations in performance is unknown, and there is a demand for consistent performance of fuel cells, etc.

[0010] The present invention has been made in consideration of the above-mentioned problems, and aims to provide a method for evaluating fluid permeability, etc., which evaluates the fluid permeability through a porous material based on the orientation of the fibers that make up the porous material. [Means for solving the problem]

[0011] The present inventors have found that the fluid permeability of the porous material that is the diffusion layer affects the performance of fuel cells, etc. Furthermore, the present inventors have found that the orientation of the fibers that make up the porous material affects the fluid permeability of the porous material that is the diffusion layer.

[0012] In order to solve the above problems, the present invention has the following features. [1] A method for evaluating fluid permeability through a porous material formed of a plurality of fibers, comprising: an imaging data acquisition step of acquiring imaging data in which the plurality of fibers of the porous material are imaged; a morphological information generating step of generating morphological information including at least a portion of the contour of the fiber imaged in the imaging data; a detection step of detecting an angle formed by the fiber imaged in the imaging data with respect to a reference direction based on the morphological information; an evaluation step of evaluating fluid permeability according to the distribution of the angles of the fibers; A method for evaluating fluid permeability, comprising: [2] The fluid permeability evaluation method described in [1], in which the morphological information generation step determines the position of the fiber in the imaging direction of the imaging data and is performed using the fibers located within a specific position range. [3] The fluid permeability evaluation method described in [1] or [2], wherein the imaging data used in the morphological information generation step is data of one of the areas divided into multiple areas of one imaging data. [4] An apparatus for evaluating fluid permeability through a porous material formed of a plurality of fibers, an acquisition unit that acquires imaging data of the porous material; a morphological information generating unit that generates morphological information including at least a portion of the contour of the fiber captured in the imaging data; a detection unit that detects an angle of the fiber captured in the imaging data with respect to a reference direction of the imaging data based on the morphological information; an evaluation unit that evaluates fluid permeability according to the distribution of the angles of the fibers; A fluid permeability evaluation device comprising: [5] A porous material formed of a plurality of fibers, A porous material in which, in imaging data in which a plurality of the fibers are imaged, the proportion of the fibers whose angles between the reference direction and the fibers are within a reference angle range that serves as a reference for showing the distribution of the angles is 30% or more. [6] An electrochemical cell including a pair of electrodes arranged opposite to each other, an electrolyte membrane disposed between the pair of electrodes, a first diffusion layer disposed between one electrode and the electrolyte membrane, and a second diffusion layer disposed between the other electrode and the electrolyte membrane, stacked together, At least one of the first diffusion layer and the second diffusion layer includes the porous material according to [5]; An electrochemical cell, wherein the porous material is arranged such that the reference direction is perpendicular to the stacking direction. [Effects of the Invention]

[0013] According to the method for evaluating the fluid permeability of a porous material of the present invention, the fluid permeability of the porous material is evaluated according to the distribution of angles that the fibers make with respect to a reference direction. This allows the permeability to be evaluated taking into account the resistance of the fluid passing through the porous material. This makes it possible to improve the accuracy of the evaluation of the fluid permeability of the porous material. [Brief explanation of the drawings]

[0014] [Figure 1] FIG. 1 is a functional block diagram of an apparatus for evaluating fluid permeability through a porous material. [Figure 2] FIG. 1 is a flow diagram showing a process flow for a method for determining the permeability of a porous material to a fluid. [Figure 3]3 is a flowchart showing a subroutine of the morphological information generating step of FIG. 2. FIG. [Figure 4] 4 is an explanatory diagram showing a processing mode in the edge detection step of FIG. 3. FIG. [Figure 5] FIG. 4 is an explanatory diagram showing a processing mode in the region dividing step of FIG. 3. [Figure 6] 4 is an explanatory diagram showing a processing mode in the line segment detection step of FIG. 3. FIG. [Figure 7] FIG. 3 is an explanatory diagram showing a processing mode of the detection step in FIG. 2; [Figure 8] FIG. 3 is an explanatory diagram showing a processing mode of the evaluation step in FIG. 2. [Figure 9] FIG. 10 is a flowchart showing a subroutine of a morphological information generating step according to the second embodiment. [Figure 10] FIG. 8 is an explanatory diagram showing the processing mode of the detection step in FIG. 7. [Figure 11] FIG. 10 is an explanatory diagram showing a processing mode of an evaluation step according to the second embodiment. [Figure 12] FIG. 1 is a schematic diagram illustrating an example of an electrochemical cell. [Figure 13] FIG. 10 is an explanatory diagram showing a processing mode of a detection step in the second embodiment. [Figure 14] FIG. 10 is an explanatory diagram showing a processing mode of an evaluation step in the second embodiment. [Figure 15] FIG. 10 is an explanatory diagram showing a processing mode of a detection step according to the fourth embodiment. [Figure 16] FIG. 10 is an explanatory diagram showing the processing mode of the evaluation step of the fourth embodiment. [Figure 17] FIG. 10 is an explanatory diagram showing the processing mode of the evaluation step of the fifth embodiment. [Figure 18] FIG. 20 is an explanatory diagram showing the processing mode of the evaluation step of the sixth embodiment. [Figure 19] 10 is a graph showing the results of a water flow test. [Figure 20] 10 is a graph showing the results of a water flow test. DETAILED DESCRIPTION OF THE INVENTION

[0015] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. Fig. 1 shows a functional block diagram of an apparatus 100 for evaluating the permeability of a fluid through a porous material. As shown in Fig. 1, the permeability evaluation apparatus 100 includes an input / output unit 10, a memory unit 20 for storing data, and a control unit 30 for controlling the operation of the permeability evaluation apparatus 100, all of which are connected via a bus 40.

[0016] The porous material is formed, for example, in the form of a sheet, from a plurality of fibers. The fibers of the porous material are not particularly limited, but examples include polyacrylonitrile carbon fibers and titanium-nickel-stainless steel porous bodies (fibers). The porous material is used, for example, as a diffusion layer in a fuel cell or the like. That is, when a porous material is used as a diffusion layer, water, oxygen, and hydrogen are fluids that permeate the porous material. The permeability evaluation device 100 evaluates the permeability of these fluids in, for example, a porous material.

[0017] The input / output unit 10 is an interface that connects external devices, namely, a camera 50 and a notification unit 60. The permeability evaluation device 100 receives input of data captured by the camera 50 via the input / output unit 10. The permeability evaluation device 100 also outputs data stored in the memory unit 20 to the notification unit 60 via the input / output unit 10.

[0018] The camera 50 is capable of capturing images of the multiple fibers that make up the porous material. For example, a digital microscope equipped with an imaging function can be used as the camera 50. The imaging direction of the camera 50 is determined depending on the direction of the fluid to be evaluated. For example, when the porous material is used as a filter, the imaging direction of the camera 50 should be the direction in which the filter is set, i.e., a direction perpendicular to the surface formed along the direction of fluid flow.

[0019] The notification unit 60 is a device that presents information to the user. Examples of the notification unit 60 include a speaker that outputs sound, a display that displays data, etc. The notification unit 60 may also be a display equipped with a speaker.

[0020] The storage unit 20 is a non-volatile memory to which data can be written. Examples of the storage unit 20 include an erasable programmable read only memory (EPROM), a hard disk drive (HDD), a solid state drive (SSD), and removable media. The storage unit 20 may also be a computer-readable recording medium such as an externally attachable memory card.

[0021] The control unit 30 is a computer including a central processing unit, a volatile memory, a non-volatile memory, etc. The control unit 30 has an acquisition unit 31 that acquires imaging data of a porous material. The control unit 30 has a morphological information generation unit 32 that generates morphological information including at least a portion of the outline of the fibers captured in the imaging data. The control unit 30 has a detection unit 33 that detects the angle that the fibers captured in the imaging data make with respect to a reference direction of the imaging data based on the morphological information. The control unit 30 has an evaluation unit 34 that evaluates the fluid permeability according to the angle of the fibers.

[0022] The acquisition unit 31, the morphological information generation unit 32, the detection unit 33, and the evaluation unit 34 realize their respective functions by executing programs stored in non-volatile memory by a central processing unit.

[0023] The acquisition unit 31 reads and acquires the imaging data from the storage unit 20 using the camera 50. The imaging data acquired by the acquisition unit 31 may be an image of the entire surface of the porous material, or may be an image of a part of the surface.

[0024] The morphological information generating unit 32 generates morphological information by performing image processing on the imaging data acquired by the acquiring unit 31. The image processing by the morphological information generating unit 32 will be described later.

[0025] The detection unit 33 determines a reference direction relative to a predetermined direction using coordinates associated with the imaging data. The reference direction is a direction arbitrarily determined by the user, and is defined, for example, as a direction along the plane (surface) of the porous material. For example, in the imaging data, the reference direction is set as a direction along the up-down direction (90°) or the left-right direction (0 or 180°). Based on the morphological information generated by the morphological information generation unit 32, the detection unit 33 detects the angle that the fibers in the imaging data make with respect to the reference direction.

[0026] The evaluation unit 34 determines the angle that the fiber detected by the detection unit 33 makes with respect to the reference direction for each fiber. The evaluation unit 34 generates evaluation data for evaluating the fluid permeability in accordance with the angle distribution of the fibers. Specifically, the evaluation unit 34 reads and acquires the reference angle range from the storage unit 20. The evaluation unit 34 generates evaluation data for evaluating the fluid permeability in accordance with the number of fibers whose angles fall within the reference angle range.

[0027] The reference angle range is a range that serves as an index showing the tendency of the angle that the fiber makes with respect to the reference direction. The reference angle range is a range that is arbitrarily determined by the user. The reference angle range may be set to a range according to the direction of the permeability of the fluid to be evaluated. The reference angle range may be, for example, a single angle range of 0 to 180° of the angle that the fiber makes with respect to the reference direction, or multiple angle ranges.

[0028] When the reference angle range is set to one angle range, it can be set, for example, to a range of 30 degrees around 90 degrees, i.e., 60 to 120 degrees. When the reference angle range is set in this way, it is possible to evaluate the fluid in a direction approximately perpendicular to the reference direction.

[0029] For example, when graphing the trend of the angle that the fibers make with respect to a reference direction with the number of fibers on the vertical axis and the angle on the horizontal axis, if an upward convex parabola is obtained, the range of angles before and after the apex of the parabola may be defined as the reference angle range.

[0030] The reference angle range may be a range divided at any ratio, such as 0 to 30°, 30 to 60°, 60 to 90°, 90 to 120°, 120 to 150°, or 150 to 180°, or may be a range divided equally. The reference angle range is stored in, for example, the storage unit 20.

[0031] Fluids for which the evaluation unit 34 evaluates the permeability include liquids such as water and aqueous solutions, and gases such as hydrogen and oxygen. When the porous material is used as a diffusion layer in a fuel cell or the like, the fluids are water, hydrogen, and oxygen. Note that these liquids and gases may contain unintentional impurities.

[0032] FIG. 2 is a process flow showing a method for evaluating the permeability of a fluid through a porous material using the permeability evaluation device 100. The process flow showing the method for evaluating the permeability of a fluid through a porous material is executed, for example, when triggered by receiving imaging data transmitted from the camera 50. The fibers of the porous material can also be seen with the naked eye. Therefore, the direction of the permeability to be evaluated can be determined by observing the porous material with the naked eye. When imaging the porous material with the camera 50, it is advisable to place the porous material along the direction of the permeability to be evaluated that is confirmed with the naked eye and then image the material.

[0033] When the control unit 30 receives the imaging data transmitted from the camera 50, it stores the imaging data in the storage unit 20. As shown in Fig. 2, the acquisition unit 31 reads out the imaging data from the storage unit 20 and executes an acquisition step (step S101).

[0034] The morphological information generating unit 32 generates morphological information using the imaging data acquired in the acquisition step of step S101, and executes the morphological information generating step (step S102). The morphological information generating unit 32 stores the generated morphological information in the storage unit 20.

[0035] The detection unit 33 detects the angle that the fibers in the image data make with respect to the reference direction based on the morphological information generated in the morphological information generation step of step S102 and the reference direction, and executes the detection step (step S103).

[0036] The evaluation unit 34 determines the proportion of the angles of the fibers detected in the detection step of step S103 that are within the reference angle range. The evaluation unit 34 stores the proportion in the storage unit 20 as evaluation data for evaluating the fluid permeability, and then executes the evaluation step (step S104).

[0037] The control unit 30 reads out the evaluation data stored in the storage unit 20 and outputs it to the notification unit 60. The notification unit 60 notifies the user of the evaluation data by, for example, displaying the evaluation data on a display.

[0038] Fig. 3 shows a subroutine of the morphological information generating step in Fig. 2. In the morphological information generating step of step S102, the morphological information generating unit 32 performs an edge detection step of detecting edges in the imaging data (step S201).

[0039] In the edge detection step of step S201, edge detection can be performed by, for example, the Canny method.

[0040] Next, the morphological information generating unit 32 divides the imaging data into predetermined regions and executes a region dividing step (step S202). In other words, the morphological information generating unit 32 generates data of one region that is divided into multiple regions from one piece of imaging data.

[0041] In the region division step of step S202, the morphological information generation unit 32 performs region division on the image data whose edges have been detected in step S201. The morphological information generation unit 32 divides the image data into uniform regions, for example. The regions to be divided may be set according to the size of the fibers that are the subject of the image data. By dividing the image data, it is possible to prevent line segments from being undetected or overdetected when the next line segment detection step of step S203 is executed.

[0042] The region division step in step S202 may be performed with a division number corresponding to the number of pixels in the image data. For example, if the image data is 1280 (pixels) x 960 (pixels), one frame can be divided into 64 (pixels) x 64 (pixels).

[0043] There is an appropriate range for the size of each frame to be divided, and if the size of each frame falls below this range, the detection rate may decrease. For example, if the image data is 1280 (pixels) x 960 (pixels), the detection rate will be lower if each frame is 32 (pixels) x 32 (pixels) than if it is 64 (pixels) x 64 (pixels).

[0044] That is, the fibers of the porous material are arranged in a bent or crossed manner, and therefore, in the image data that has undergone the edge detection step of step S201, the pixels that indicate the edges, which are the outlines of the fibers, are arranged in complex shapes rather than simple straight lines.

[0045] In the line segment detection step of step S203, line segments are detected, for example, according to the number of points arranged in a straight line. The image data used in the line segment detection step is finely set by the area division step of step S202. This makes it possible to reduce the occurrence of so-called overdetection, in which irrelevant point groups are detected as line segments, and so-called non-detection of line segments, in which point groups that should be detected as line segments are not detected correctly.

[0046] By performing the region division step in step S202, it becomes possible to process the image data to a size suitable for the point cloud to be detected as line segments. As a result, in the line segment detection step in step S203, false detections due to fiber arrangement patterns such as bending and crossing can be reduced, and detection accuracy can be improved.

[0047] Next, the morphological information generating unit 32 detects line segments from the captured image data divided in step S202, and executes a line segment detection step (step S203).

[0048] In the line segment detection step of step S203, line segments are detected by, for example, performing a Hough transform on the image data divided in the region division step of step S202.

[0049] Fig. 4 shows the processing mode in the edge detection step of step S201. The white lines shown in Fig. 4 are the outlines of the fibers detected in the edge detection step, that is, the edges.

[0050] The morphological information generation unit 32, for example, converts the imaging data into a grayscale image and detects the edges of the binarized fibers. Specifically, when the edge detection step of step S201 is performed, morphological information is generated according to the sharpness of the fiber contours. For example, when the lens is focused on the surface layer, fibers further back on the optical axis of the lens than the surface layer appear blurred. In other words, the sharpness of the contours of fibers further back on the optical axis of the lens than the surface layer is reduced. In the edge detection step of step S201, if the sharpness of the contours is lower than a predetermined threshold, it is recommended not to detect them as edges.

[0051] The number of fibers within the reference angle range is roughly the same at any position in the imaging direction corresponding to the thickness direction of the porous material. Therefore, if the orientation direction of fibers on the surface of a porous material can be evaluated, it becomes possible to evaluate the fluid permeability of the porous material. In other words, by extracting fibers on the surface of a porous material and generating morphological information, it is possible to reduce the processing load and noise compared to when extracting fibers throughout the entire porous material and generating morphological information. As a result, the accuracy of the morphological information can be improved, and the detection accuracy of the subsequent detection step can be improved.

[0052] Fig. 5 shows the processing mode in the region division step of step S202. In Fig. 5, the regions divided by two-dot chain lines are regions divided by the region division step. In the example shown in Fig. 5, each region is divided into 5 rows and 4 columns.

[0053] The regions divided in the region dividing step are preferably set so that the pixels of the image data are divided equally. For example, if the pixels of the image data are h pixels vertically (h is an arbitrary value) and w pixels horizontally (w is an arbitrary value), the upper limit of the region divided by the morphological information generating unit 32 is preferably set to h / 2 pixels vertically and w / 2 pixels horizontally. By setting the upper limit of the region divided in this way, it is possible to divide the image data into at least two regions vertically and horizontally.

[0054] FIG. 6 shows the processing mode in the line segment detection step of step S203. The thick black line shown in FIG. 6 is an example of a line segment detected in the line segment detection step of step S203. The morphological information generation unit 32 creates a straight line using the coordinates of two points of the line segment detected by the Hough transform. In this way, the morphological information generation unit 32 generates the fiber line segments as morphological information.

[0055] The dashed-dotted arrow shown in Fig. 6 is the reference direction DX1, which is set to the left-right direction in the imaging data in Fig. 6.

[0056] FIG. 7 shows the processing mode of the detection step of step S103. The dashed-dotted arrows shown in FIG. 7 indicate the reference direction DX1. The solid lines shown in the image data 70 in FIG. 7 indicate fiber line segments 71 detected by Hough transform. The detection unit 33 determines the angle θ that the fiber line segments 71 detected by Hough transform make with respect to the reference direction DX1. The detection unit 33 determines this angle for, for example, all of the fiber line segments 71 detected by Hough transform in the image data 70.

[0057] That is, in the detection step of step S103, the angle θ that each fiber line segment 71 imaged in the imaging data 70 makes with respect to the reference direction DX1 is detected based on the morphological information generated in the morphological information generation step of step S102.

[0058] 8 shows the processing mode of the evaluation step of step S104. In the detection step of step S104, the evaluation unit 34 sets a predetermined angle range, for example, between 0 and 180 degrees. The predetermined angle range can be arbitrarily set by the user, and can be set in increments of 10 degrees, for example.

[0059] The evaluation unit 34 acquires each angle θ that a fiber segment makes with respect to the reference direction DX1. The evaluation unit 34 determines to which angle range a given angle θ belongs. The evaluation unit 34 performs this determination for each angle θ. The evaluation unit 34 counts the number of angles θ that are determined to fall within that angle range. The evaluation unit 34 may count the number of angles θ that are determined to fall within that angle range for all of the imaging data divided into regions in step S202.

[0060] The evaluation unit 34 refers to the reference angle range RR stored in the storage unit 20 and determines the number of fibers that are within the reference angle range RR. The reference angle range RR can be set to, for example, 60 to 120°. The reference angle range RR is the area indicated by the dashed line in FIG. 8.

[0061] In Figure 8, the proportion of fiber segments that form an angle of 90 to 100 degrees with respect to the reference direction is higher than the other proportions. Also, in Figure 8, the graph is convex upward, with a peak in the angle range of 90 to 100 degrees. Furthermore, the number of fibers within the reference angle range RR is greater than the number of fibers in other angle ranges.

[0062] The resistance of a fluid to permeate a porous material decreases in the direction along the fiber orientation. In other words, the fluid permeability is recognized as high in the direction along the fiber orientation. Therefore, in the example shown in FIG. 8, the fluid permeability of the porous material is evaluated as high in the direction approximately perpendicular to the reference direction. The evaluation unit 34 creates a histogram such as that shown in FIG. 8 as evaluation data and stores it in the memory unit 20.

[0063] 8, the reference angle range is set to 60 to 120°. The setting of the reference angle range is not limited to this, and multiple reference angle ranges may be set. For example, a first reference angle range may be set to 0 to 30°, a second reference angle range to 30 to 60°, a third reference angle range to 60 to 90°, a fourth reference angle range to 90 to 120°, a fifth reference angle range to 120 to 150°, and a sixth reference angle range to 150 to 180°.

[0064] According to this aspect, for the first reference angle range, it is possible to evaluate the fluid permeability in a direction along the reference direction. Furthermore, for the second reference angle range, it is possible to evaluate the fluid permeability in a direction where a line segment slopes upward to the right relative to the reference direction. For the third reference angle range, it is possible to evaluate the fluid permeability in a direction perpendicular to the reference direction. For the fourth reference angle range, it is possible to evaluate the fluid permeability in a direction where a line segment slopes downward to the right relative to the reference direction.

[0065] In this way, when a plurality of reference angle ranges are set, the evaluation unit 34 may classify the images into categories set according to the plurality of reference angle ranges, calculate the cumulative frequency according to the category, and generate the evaluation data. Furthermore, the evaluation unit 34 may calculate the relative frequency of these to generate the evaluation data.

[0066] When generating the evaluation data, the evaluation unit 34 may determine the orientation direction of the main fiber line segments depending on the bias of the line segment angle θ. For example, when first to fourth reference angle ranges are set, the orientation direction of the main fiber line segments can be determined as a direction corresponding to a reference angle range to which 35% or more of the angle θ belongs within these reference angle ranges. Note that the bias of the line segment angle θ when determining the orientation direction of the main fiber line segments can be set arbitrarily by the user.

[0067] The vertical axis in Figure 8 represents the number of counted line segments forming an angle θ. For example, if fibers are arranged in a bent state in a porous material, multiple line segments may be detected in the imaging data even for a single fiber. In other words, if the number of fibers is used as the vertical axis, it is difficult to consider the influence of such fiber bending. In other words, by using the number of counted line segments as the vertical axis instead of the number of fibers, it is possible to appropriately evaluate permeability even when fibers have multiple orientations, such as bending.

[0068] In this embodiment, an example has been described in which the number of fibers within the reference angle range is determined. The evaluation by the evaluation unit 34 is not limited to this example, and for example, the number of fibers within the reference angle range may be used to perform statistical processing to generate evaluation data. Examples of such statistical processing include standard deviation (3σ method).

[0069] In the above-described embodiment, the region division step of step S202 is a step that can be performed arbitrarily depending on the embodiment. That is, if the line segment detection step of step S203 is sufficiently accurate, the region division step does not need to be performed.

[0070] In addition, in the morphological information generation step of step S102, an example has been described in which line segments derived from the fiber contours are detected. However, the morphological information may include at least a portion of the fiber contours. For example, the edge of the fiber contour may be generated as the morphological information. In this case, in the detection step of step S103, the angle between the fiber edge and the reference direction may be detected.

[0071] As described above, according to the fluid permeability evaluation method of the present invention, the fluid permeability of a porous material is evaluated according to the number of fibers that fall within the reference angle range. This allows the permeability to be evaluated taking into account the resistance of the fluid passing through the porous material. Therefore, it is possible to improve the accuracy of the evaluation of the fluid permeability of the porous material.

[0072] In the above embodiment, an example has been described in which the region division step is executed in the morphological information generation step of Fig. 3. The region division step is an optional step and may be omitted depending on the embodiment.

[0073] In the above-described embodiment, an example of evaluating fluid permeability using a reference angle range has been described. The evaluation of fluid permeability may be performed according to the distribution of fiber angles, and any reference angle range may be used. For example, when the trend of the angle formed by the fibers relative to the reference direction is graphed with the number of fibers on the vertical axis and the angle on the horizontal axis, if an upwardly convex parabola is obtained, the distribution of the fiber angles can be determined. A porous material can be evaluated as having high fluid permeability in the convex direction.

[0074] (Second embodiment) In the above-described embodiment, an example has been described in which fiber line segments are detected using a Hough transform in the morphological information generating step. However, the morphological information generating step is not limited to this example, and fiber line segments may be detected using a Line Segment Detector (LSD). Hereinafter, the same components as those in the first embodiment will be assigned the same reference numerals and descriptions thereof will be omitted.

[0075] Fig. 9 shows a subroutine of the morphological information generating step according to the second embodiment. As shown in Fig. 9, in the morphological information generating step of step S102, the morphological information generating unit 32 performs a grayscaling step of grayscaling the imaging data (step S301).

[0076] Next, the morphological information generation unit 32 detects line segments from the imaging data grayscaled in step S301 and executes a line segment detection step (step S302). In the line segment detection step of step S302, fiber line segments are detected using, for example, a Line Segment Detector (LSD).

[0077] Fig. 10 shows the processing mode in the line segment detection step of step S302. The thick black lines shown in Fig. 10 are examples of line segments detected in the line segment detection step of step S302. The morphological information generation unit 32 detects line segments using a Line Segment Detector (LSD). The morphological information generation unit 32 generates the detected line segments as morphological information.

[0078] Fig. 11 shows the processing mode of the evaluation step of step S104 in this embodiment. In Fig. 11, the proportion of fiber line segments that form an angle of 90 to 100 degrees with respect to the reference direction is higher than the other proportions. Also, in Fig. 11, the graph is convex upward, with the angle range of 90 to 100 degrees being the peak.

[0079] In the example shown in Fig. 11, the reference angle range RR is set to 60 to 120°. The reference angle range RR is the area indicated by the dashed line in Fig. 11. The number of fibers within the reference angle range RR is greater than the number of fibers in other angle ranges.

[0080] 11, the fluid permeability of the porous material is evaluated as high in the direction substantially perpendicular to the reference direction. The evaluation unit 34 creates a histogram as shown in FIG. 11 as evaluation data and stores it in the storage unit 20.

[0081] The area used for line segment detection by LSD is narrower than the area division performed in the above-mentioned embodiment. Therefore, it is possible to reduce undetected and overdetected areas compared to when detecting line segments using Hough transform. Therefore, by detecting fiber line segments using LSD, it is possible to improve the accuracy of evaluating fluid permeability.

[0082] In the above-described embodiment, Hough transform and LSD are used to detect fiber line segments, but the present invention is not limited to these embodiments as long as fiber line segments can be detected from the imaging data.

[0083] (Third embodiment) The porous material described in the above embodiments is preferably used as a diffusion layer of an electrochemical cell. FIG. 12 is a schematic diagram showing an example of an electrochemical cell (a solid polymer water electrolysis cell). The diffusion layer used in the third embodiment is a porous transport layer. As shown in FIG. 12, an electrochemical cell 80 includes a pair of electrodes 81a and 81b arranged opposite each other and an electrolyte membrane 82 disposed between the pair of electrodes 81a and 81b. The electrochemical cell 80 includes a first diffusion layer 83a disposed between one electrode, the oxygen electrode 81a, and the electrolyte membrane 82, and a second diffusion layer 83b disposed between the other electrode, the hydrogen electrode 81b, and the electrolyte membrane 82. The electrochemical cell 80 includes a stack of the oxygen electrode 81a, the first diffusion layer 83a, the electrolyte membrane 82, the second diffusion layer 83b, and the hydrogen electrode 81b, in this order.

[0084] The oxygen electrode 81a and the hydrogen electrode 81b are connected to a power source 85. The oxygen electrode 81a corresponds to the anode, and the hydrogen electrode 81b corresponds to the cathode. Therefore, the power source 85 is configured to supply electrons to the hydrogen electrode 81b.

[0085] The electrolyte membrane 82 may be made of a polymer material that is electrically conductive in a wet state. The electrolyte membrane 82 may be, for example, a proton-conductive ion exchange membrane made of a fluororesin. An example of such an ion exchange membrane may be a perfluorosulfonic acid-based cation exchange membrane. Alternatively, the electrolyte membrane 82 may be an anion-conductive ion exchange membrane. An example of an anion-conductive ion exchange membrane is Sustainion (product name, manufactured by Dioxide Materials).

[0086] 12, a catalyst layer 84 is provided between a first diffusion layer 83a and an electrolyte membrane 82. In addition, a catalyst layer 84 is provided between a second diffusion layer 83b and an electrolyte membrane 82.

[0087] The catalyst layer 84 is formed by supporting a catalyst on a conductive carrier. Examples of the catalyst include iridium, platinum, platinum alloys, etc. Examples of the carrier include carbon particles, etc.

[0088] At least one of the first diffusion layer 83 a and the second diffusion layer 83 b is made of the porous material described in the above embodiment. In this embodiment, the first diffusion layer 83 a and the second diffusion layer 83 b are made of the porous material described in the above embodiment.

[0089] The first diffusion layer 83a and the second diffusion layer 83b are arranged in the stacking direction DY of the electrochemical cell 80 so as to have the same fluid permeability as that evaluated in the above-described embodiment. That is, the first diffusion layer 83a and the second diffusion layer 83b are arranged so that their reference direction is perpendicular to the stacking direction DY.

[0090] In the porous material of the first diffusion layer 83a and the second diffusion layer 83b, the ratio of fibers whose angles with respect to the reference direction are within the reference angle range in the image data of a plurality of fibers is preferably 30% or more, more preferably 50% or more, and even more preferably 70% or more. There is no particular upper limit to the ratio of such fibers, and it is preferable to set it as the limit value that can be produced as fibers.

[0091] By making the proportion of the fibers 30% or more, it is possible to make the fluid permeability uniform, thereby reducing variations in the performance of the electrochemical cell.

[0092] As described above, in the electrochemical cell of the present invention, the ratio of fibers whose angles with respect to the fluid flow direction are within the reference angle range is 30% or more. This makes it possible to provide an electrochemical cell with reduced resistance to fluid passing through the porous material. Therefore, it is possible to improve the performance of the electrochemical cell. [Example]

[0093] (Fluid permeability evaluation test) The fluid permeability of the porous material was evaluated using the image data of the porous material. For this evaluation, the fluid permeability evaluation method and the fluid permeability evaluation device described above were used.

[0094] The porous material was formed in A4 size (210 mm x 297 mm) and then cut to 50 mm x 100 mm. That is, the cut porous material was formed into a rectangular shape when viewed from above. Hereinafter, the short direction of the porous material will also be referred to as the 50 mm direction. The long direction of the porous material will also be referred to as the 100 mm direction.

[0095] A digital microscope (VHX-6000 (manufactured by Keyence Corporation)) was used to image the porous material. Next, the image data was subjected to a grayscale process. The grayscaled image data was used in the image data acquisition step.

[0096] In the morphological information generation step, grayscaled image data was subjected to Hough transform processing to detect fiber line segments and generate morphological information, resulting in Examples 1 and 2. Furthermore, grayscaled image data was subjected to LSD to detect fiber line segments and generate morphological information, resulting in Examples 3 and 4.

[0097] In the detection step, angles of the line segments of the fibers detected in the morphological information generation step were detected. In the evaluation step, a histogram was created as evaluation data by analyzing angles that the line segments make with respect to a reference direction.

[0098] In the morphological information generation step in Examples 1 and 2, an edge detection step was performed using the Canny method with threshold values ​​of 150 and 300. Then, in the region division step, the region was divided into 64 pixels vertically and horizontally. In the line segment detection step, line segment detection was performed using Hough transform.

[0099] In the morphological information generating step in Examples 3 and 4, line segment detection was performed using grayscaled image data.

[0100] FIG. 6 shows the line segment detection mode in Example 1. FIG. 8 is a histogram of Example 1. FIG. 13 shows the line segment detection mode in Example 2. FIG. 14 is a histogram of Example 2. FIG. 10 shows the line segment detection mode in Example 3. FIG. 11 is a histogram of Example 3. FIG. 15 shows the line segment detection mode in Example 4. FIG. 16 is a histogram of Example 4.

[0101] 13 and 15, the reference direction DX2 is indicated by a dashed line. In Examples 2 and 4, the up-down direction in the imaging data is set as the reference direction DX2.

[0102] 14 and 16, in Examples 2 and 4, the reference angle ranges were set as follows: 0 to 30° was set as the first reference angle range RR1, 30 to 60° was set as the second reference angle range RR2, 60 to 90° was set as the third reference angle range RR3, and 90 to 120° was set as the fourth reference angle range RR4, 120 to 150° was set as the fifth reference angle RR5, and 150 to 180° was set as the sixth reference angle RR6.

[0103] As shown in FIG. 14, the first reference angle range RR1, the second reference angle range RR2, and the sixth reference angle range RR6 had higher counts than the other reference angle ranges.

[0104] Furthermore, as shown in FIG. 16, the first reference angle range RR1 and the sixth reference angle range RR6 had higher count numbers than the other reference angle ranges.

[0105] That is, the histograms shown in Fig. 14 and Fig. 16 are concave graphs. Therefore, in the example of Fig. 14, it was found that the first reference angle range RR11, the second reference angle range RR2, and the sixth reference angle range RR6 are the main fiber orientation directions. Also, in the example of Fig. 16, it was found that the first reference angle range RR11 and the sixth reference angle range RR6 are the main fiber orientation directions. In other words, in both cases, it can be evaluated that the up-down direction of the imaging data is the main fiber orientation direction.

[0106] As described above, as shown in FIGS. 8, 11, 14, and 16, it was found that in Examples 1 to 4, the distribution of angles that the fiber segments make with the reference direction could be obtained satisfactorily. [Example]

[0107] (Area division comparison test) The difference in line detection effect due to the region division step was compared for the image data used in the line detection step using LSD.

[0108] Examples 3 and 4 show examples in which the line segment detection step was performed using LSD after the region division step was performed. In the region division step of Example 3, region division was performed using a 64 pixel angle. In the region division step of Example 4, region division was performed using a 640 pixel angle. The results of counting the number of fibers for each angle range for Examples 3 and 4 are shown in Table 1.

[0109] [Table 1]

[0110] As shown in Table 1, in both Examples 3 and 4, a sufficient number of counts was obtained. [Example]

[0111] (Area division comparison test) The difference in the line segment detection effect by the area division step was compared for the image data used when executing the line segment detection step by Hough transform.

[0112] Examples 5 and 6 are examples in which the line segment detection step is performed by Hough transform after the region division step is performed. In the region division step of Example 5, region division is performed using a 64 pixel square. In the region division step of Example 6, region division is performed using a 640 pixel square. In addition, Example 7 is an example in which the line segment detection step is performed by Hough transform without performing the region division step.

[0113] Fig. 17 shows a histogram of Example 5. Fig. 18 shows a histogram of Example 7. As shown in Figs. 17 and 18, both histograms reveal that the fourth reference angle range RR4 is the main fiber orientation direction.

[0114] For Examples 5 to 7, the number of fibers in each angle range was counted, and the results are shown in Table 2. [Table 2]

[0115] As shown in Table 2, when Examples 5 to 7 are compared, the count number decreases as the region division size increases. In other words, as the region division size increases, there is a tendency for so-called undetected line segments to increase.

Example

[0116] (Water flow test) The water flow rate when a predetermined water pressure was applied to the porous material was measured. The water pressures applied to the porous material were 0.1 MPa, 0.2 MPa, and 0.3 MPa. Also, for the measured flow rates, the flow rate per 1 mm thickness of the porous material (ml / min / mm) was used. In measuring the flow rate, a gasket and the porous material were installed on the jig (gasket <PTL). The porous material was installed by fastening with an arbitrary load.

[0117] FIG. 19 shows a graph when a water flow test was performed in the 50 mm direction (the short side direction of the porous material) for the porous materials used in Examples 1 and 2. That is, in the test of FIG. 19, the test was performed with the water flow direction as the short side direction of the porous material.

[0118] FIG. 20 shows a graph when a water flow test was performed in the 100 mm direction (the long side direction of the porous material) for the porous materials used in Examples 1 and 2. That is, in the test of FIG. 19, the test was performed with the water flow direction as the long side direction of the porous material.

[0119] As shown in FIGS. 19 and 20, it was found that the water flow rate in the short side direction of the porous materials used in Examples 1 and 2 is more than three times that in the long side direction. That is, it was found that the porous materials used in Examples 1 and 2 allow fluid to flow easily in the short side direction and hardly allow fluid to flow in the long side direction. Also, it was found that the porous materials used in Examples 1 and 2 have sufficient fluid permeability in their short side direction.

[0120] Furthermore, no significant difference in fluid permeability was observed between Examples 1 and 2. Therefore, by using a porous material in this manner as a diffusion layer of an electrochemical cell, it is possible to suppress variations in the performance of the electrochemical cell. That is, by appropriately arranging a porous material whose fluid permeability has been evaluated by the fluid permeability evaluation method of the present invention in the direction of fluid flow according to the evaluation mode, it becomes possible to efficiently supply fluid to the electrode catalyst. As a result, it is possible to improve the current and voltage characteristics of fuel cells and the like. [Explanation of symbols]

[0121] 100 Permeability evaluation device 30 Control Unit 31 Acquisition Department 32 Shape information generation unit 33 Detection unit 34 Evaluation Department 50 cameras 80 Electrochemical Cells 81a One electrode 81b Other electrode 82 Electrolyte membrane 83a First diffusion layer 83b Second diffusion layer DX1 Reference direction DX2 reference direction

Claims

1. A method for evaluating fluid permeability through a porous material formed of a plurality of fibers, comprising: an imaging data acquisition step of acquiring imaging data in which the plurality of fibers of the porous material are imaged; a morphological information generating step of generating morphological information including at least a portion of the contour of the fiber imaged in the imaging data; a detection step of detecting an angle formed by the fiber imaged in the imaging data with respect to a reference direction based on the morphological information; an evaluation step of evaluating fluid permeability according to the distribution of the angles of the fibers; A method for evaluating fluid permeability, comprising:

2. The method for evaluating fluid permeability according to claim 1 , wherein the morphological information generating step generates morphological information according to a degree of definition of the contours of the fibers.

3. 3. The method for evaluating fluid permeability according to claim 1, wherein the imaging data used in the morphological information generating step is data for one of a plurality of regions divided into one imaging data set.

4. An apparatus for evaluating fluid permeability through a porous material formed of a plurality of fibers, an acquisition unit that acquires imaging data of the porous material; a morphological information generating unit that generates morphological information including at least a portion of the contour of the fiber captured in the imaging data; a detection unit that detects an angle of the fiber captured in the imaging data with respect to a reference direction of the imaging data based on the morphological information; an evaluation unit that evaluates fluid permeability according to the distribution of the angles of the fibers; A fluid permeability evaluation device comprising:

5. A porous material formed of a plurality of fibers, A porous material in which, in imaging data in which a plurality of the fibers are imaged, the proportion of the fibers whose angles between a reference direction and the fibers are within a reference angle range that serves as a reference for showing the distribution of the angles is 30% or more.

6. An electrochemical cell including a pair of electrodes arranged opposite to each other, an electrolyte membrane disposed between the pair of electrodes, a first diffusion layer disposed between one electrode and the electrolyte membrane, and a second diffusion layer disposed between the other electrode and the electrolyte membrane, stacked together, At least one of the first diffusion layer and the second diffusion layer includes the porous material according to claim 5 ; An electrochemical cell, wherein the porous material is arranged such that the reference direction is perpendicular to the stacking direction.

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