A method for determining the distribution of conductive agents and / or binders based on the morphology of secondary battery electrodes.

Abstract

This application relates to a method for determining the distribution of conductive agents and / or binders based on the morphology of secondary battery electrode sheets, belonging to the field of secondary battery electrode material testing technology. This application identifies conductive agents and / or binders by obtaining SEM microstructure images of the detection area on the secondary battery electrode sheet, and determines the distribution effect of the conductive agents and / or binders based on their area in the detection area. This method can directly obtain the distribution of conductive agents and / or binders in the detection area. By selecting different detection areas, the uniformity of the distribution of conductive agents and / or binders in the electrode sheets of the secondary battery can be detected, thereby confirming the distribution state of conductive agents and / or binders in the secondary battery electrode sheets, providing theoretical support for the performance research and improvement of secondary batteries, as well as the improvement of manufacturing processes.

Description

Technical Field

[0001] This invention belongs to the field of secondary battery electrode material testing technology, specifically relating to a method for determining the distribution of conductive agents and / or binders based on the morphology of secondary battery electrode sheets. Background Technology

[0002] The distribution of binders and conductive agents has a significant impact on the performance of secondary battery electrode sheets. This is especially true for cathode sheets, where the electronic conductivity of active materials such as lithium cobalt oxide is relatively low, necessitating the use of conductive agents to improve conductivity. Therefore, the distribution effect of conductive agents and binders is a key factor in the conductivity of the cathode sheet and largely determines the internal resistance performance of the lithium-ion battery. Cathode materials are characterized by hygroscopicity, high alkalinity, and specific gradations, making them prone to high viscosity and sedimentation during slurry preparation, leading to particle agglomeration and floating problems. Therefore, a microscopic-level evaluation of the binder and conductive network distribution is crucial.

[0003] Currently, there is limited information available on direct characterization methods for the distribution of binders and conductive agents in this field. For example, existing techniques involve peeling back the current collector interface to test the fluorine (F) distribution and then using EDS to assess the total F content on the current collector side of the secondary battery electrode sheet to evaluate the flotation of binders and conductive agents. This method is affected by interfacial peeling forces and only reflects the content at the interface, providing a partial characterization area and failing to reflect the overall distribution effect of the secondary battery electrode sheet. Existing techniques also propose a method for detecting the distribution of conductive agents in secondary battery electrode sheets by adding phosphor during slurry preparation and then performing fluorescence detection on the prepared electrode sheet. This method requires the prior preparation of secondary battery electrode sheets containing phosphor, which is a complex process, and the addition of phosphor may affect the distribution of conductive agents and binders. Therefore, this method cannot directly detect the distribution effect of conductive agents and binders in secondary battery electrode sheets. Summary of the Invention

[0004] In view of this, this application provides a method for determining the distribution of conductive agents and / or binders based on the morphology of secondary battery electrode sheets. By acquiring SEM microstructure images of the detection area on the secondary battery electrode sheet, the conductive agents and / or binders are identified, and their distribution effect is determined based on their area within the detection area. This method can directly obtain the distribution of conductive agents and / or binders in the detection area. By selecting different detection areas, the agglomeration, floating, or uniform distribution of conductive agents and / or binders in the secondary battery electrode sheet can be determined, thereby identifying the causes of distribution problems and providing a theoretical basis for improving the manufacturing process of secondary battery electrode sheets.

[0005] The method for determining the distribution of conductive agents and / or binders based on the morphology of secondary battery electrode sheets provided in this application employs the following technical solution:

[0006] A method for determining the distribution of conductive agents and / or binders based on the morphology of a secondary battery electrode sheet, the method comprising the following steps: Step S100, selecting a detection area from the secondary battery electrode sheet and obtaining a SEM microstructure image of the detection area; Step S200, identifying the detection substance in the SEM microstructure image and obtaining the area of ​​the detection substance; Step S300, determining the distribution effect of the detection substance based on the area of ​​the detection substance; wherein the detection substance is a conductive agent and / or binder. This application, by obtaining a SEM microstructure image of the detection area on the secondary battery electrode sheet, identifies the location of the conductive agent and / or binder on the SEM microstructure image, thereby qualitatively determining the distribution of the conductive agent and / or binder; furthermore, by using the area of ​​the conductive agent and / or binder within the detection area, a quantitative evaluation of the distribution effect of the conductive agent and / or binder can be achieved. This method can comprehensively assess the distribution effect of conductive agents and / or binders on the electrode sheets of secondary batteries. For cases of uneven distribution, analysis of the area data of conductive agents and / or binders in different detection areas can determine the causes of uneven distribution from two perspectives: floating and agglomeration. This provides a theoretical basis for further optimizing the preparation process of conductive agents and / or binders, as well as the electrode sheets, and improving the uniformity of conductive agent and / or binder distribution. Furthermore, by determining the distribution effect of conductive agents and / or binders in the electrode sheets of secondary batteries, the conductivity and / or internal resistance performance of the secondary battery can be analyzed and evaluated, providing theoretical support for improving secondary battery performance.

[0007] For example, the electrode sheets for secondary batteries can be directly prepared or obtained from disassembly of secondary batteries. Further, after obtaining the electrode sheets from the secondary battery, the electrode sheets are cleaned with dimethyl carbonate (DMC) and then the distribution of conductive agents and / or binders is detected. Optionally, the cleaning is performed 1 to 3 times, with each cleaning session lasting 1 to 2 hours.

[0008] Preferably, the detection area is selected from the surface of the secondary battery electrode sheet or a cross-section of the secondary battery electrode sheet cut along its thickness direction. When the detection area is selected from the cross-section of the secondary battery electrode sheet cut along its thickness direction, the floating and uniform distribution of the conductive agent and / or binder within the detection area can be determined by the area data of the conductive agent and / or binder within the detection area; when the detection area is selected from the surface of the secondary battery electrode sheet, the agglomeration of the conductive agent and / or binder within the detection area can be determined by the area distribution data of the conductive agent and / or binder within the detection area.

[0009] For example, the cross-section can be obtained by cutting the secondary battery electrode sheets using an Ar ion beam cutter or a focused ion beam (FIB) cutter.

[0010] Preferably, the length of the detection area is L, and the value of L ranges from 1 mm to 5 mm; the width of the detection area is W, and the value of W ranges from 40 μm to 1000 μm. In this application, the length direction of the detection area refers to the direction of the longer side of the detection area, and the width direction of the detection area refers to the direction of the shorter side of the detection area. When the detection area is selected from a cross-section cut along the thickness direction of the secondary battery electrode sheet, the width direction of the detection area is the thickness direction of the secondary battery electrode sheet. The method of this application can comprehensively reflect the distribution of conductive agent and / or binder on the secondary battery electrode sheet by selecting the range of length and width of the two-dimensional selection area.

[0011] Preferably, step S200 includes: sequentially performing grayscale processing and thresholding on the SEM microstructure image to identify the detection substance and obtain the area of ​​the detection substance. Grayscale processing combined with thresholding can highlight and enhance the distribution image of conductive agents and / or binders in the SEM microstructure image, ensuring comprehensive identification and calculation of the area of ​​conductive agents and / or binders, and improving the accuracy and precision of detection.

[0012] For example, the detection substance in the detection area can be identified by marking an example sample of the substance to be detected, and then using the machine recognition function of image processing software, such as ImageJ software.

[0013] Preferably, the grayscale processing further includes blurring the SEM microstructure image before processing; blurring can reduce noise in the SEM microstructure image and improve the accuracy of identifying conductive agents and / or binders.

[0014] Preferably, the threshold selection range for the threshold division is A to B, where the value range of A is 0≤A≤80, the value range of B is 40≤B≤200, and A<B.

[0015] Preferably, the distribution effect includes an aggregation effect; in step S300, determining the distribution effect of the detection substance based on its area includes: obtaining the area distribution of the detection substance based on its area, and determining the aggregation degree t of the detection region based on Equation I; t = N B / N A Equation I; In Equation I, N B N represents the total area of ​​the large-area detected substance in the detection region within the area distribution. A In the area distribution, S' is the total area of ​​the detected substance in the detection region; the area of ​​the large-area detected substance is S', where S' ≥ h, and the value of h ranges from 50 to 300 μm. 2If t ≤ T, it is determined that the conductive agent and / or binder have not agglomerated; if t > T, it is determined that the conductive agent and / or binder have agglomerated; the value of T ranges from 0.1% to T ≤ 10%. In this application, T is a standard value for determining the degree of agglomeration of the conductive agent and / or binder. By comparing it with the value of T, it is possible to quickly determine whether the conductive agent and / or binder in the electrode sheet of the secondary battery has agglomerated.

[0016] Preferably, the distribution effect includes a floating effect; in step S300, determining the distribution effect of the detected substance based on its area includes: obtaining the content of the detected substance w' = S' / S based on its area. A Where S' is the area of ​​the substance to be detected in the detection region, S A The total area of ​​the detection zone is used to determine the buoyancy effect of the detection zone based on the content of the detected substance.

[0017] Preferably, the distribution effect includes a floating effect; when the detection area is a cross-section cut along the thickness direction of the secondary battery electrode sheet, in step S300, determining the distribution effect of the detection substance based on the area of ​​the detection substance includes: step S301, dividing the detection area along the thickness direction of the secondary battery electrode sheet into n layers, respectively denoted as the 1st thickness layer, the 2nd thickness layer, ..., the nth thickness layer; the value of n is in the range of n≥2; step S302, determining the content w of the detection substance in each layer according to formula II and / or formula III. i Based on the content w of the detected substance i To determine the buoyancy effect of the conductive agent and / or binder; i =S i / S A Equation II; In Equation II, S i S is the area of ​​the detection material in the i-th thickness layer. A Let w be the total area of ​​the i-th thickness layer, where i ranges from 1 to i and from n to n; i =H i / 255 Formula III; In Formula III, H i Let be the average gray value of the detected material in the i-th thickness layer.

[0018] Preferably, the value of n is in the range of 2 ≤ n ≤ 40; and / or; the thickness of each layer is d, and the value of d is in the range of 2 μm ≤ d ≤ 30 μm. The thickness d of each layer can be the same or different, that is, when dividing along the thickness direction of the secondary battery electrode sheet, it can be divided uniformly or unevenly; preferably, the thickness d of each layer is the same. Ensuring that the thickness of each layer is uniform can make the detection results more accurate.

[0019] Preferably, the step based on the content w of the detected substance iTo determine the buoyancy effect of the conductive agent and / or binder, including: if w i ≤P×w q If the distribution of the conductive agent and / or adhesive is uniform, then the distribution effect is determined to be uniform; otherwise, the distribution effect is determined to be non-uniform. P is the uniformity coefficient, and the value of P ranges from 1.0 to 1.5. q w represents the average content of the detected substance from the 1st thickness layer to the nth thickness layer. q =∑w i / n.

[0020] Preferably, the step based on the content w of the detected substance i Determining the distribution effect of the conductive agent and / or binder includes: obtaining the buoyancy coefficient k according to Equation IV; k = w x / w s In Equation IV, w s This represents the average content of the detected substance from the 1st thickness layer to the sth thickness layer, where s is an integer and n / 2 ≤ s < (n / 2 + 1), w s =∑w i / s, where the value of i ranges from 1 to i and from s to s; w x w represents the average content of the detected substance from the (s+1)th thickness layer to the nth thickness layer. x =∑w i / (ns), where i is in the range of s≤i≤n; the first thickness layer is the layer closest to the current collector; the nth thickness layer is the layer farthest from the current collector; if k≤M, it is determined that the conductive agent and / or adhesive has not floated; if k>M, it is determined that the conductive agent and / or adhesive has floated; the value of M is in the range of 1.0≤M≤2.0.

[0021] For example, the specific values ​​of T, P, and M in this application can be determined based on the performance requirements of the electrode plates of the secondary battery, such as the requirements for membrane resistance performance. Membrane resistance performance is related to the distribution effect of the conductive agent and / or binder. When the degree of agglomeration, distribution uniformity, or buoyancy coefficient exceeds a certain level, it will lead to deterioration of the membrane resistance performance, which may prevent it from meeting the performance requirements for use in secondary batteries. Therefore, the qualified standard values ​​of T, P, and M can be determined based on the performance requirements of the electrode plates of the secondary battery.

[0022] The method for determining the distribution of conductive agents and / or binders based on the morphology of secondary battery electrode sheets provided in this application has the following advantages:

[0023] First, the SEM microstructure images of the two-dimensional detection area on the electrode sheet of the secondary battery are analyzed to identify the conductive agent and / or binder to be tested from a microscopic perspective. By analyzing the area data of the conductive agent and / or binder in the SEM microstructure images, the distribution effect of the conductive agent and binder in the electrode sheet of the secondary battery under test can be accurately and intuitively determined. This method can form a standardized judgment method, which is conducive to its widespread application and has important significance for the performance measurement of lithium-ion batteries.

[0024] Secondly, this method can achieve different detection purposes by selecting different detection areas. For example, the detection area can be selected from the surface of the secondary battery electrode to determine the agglomeration of the conductive agent and / or binder, and the detection area can be selected from the cross section cut along the thickness direction of the secondary battery electrode to determine the floating and distribution uniformity of the conductive agent and / or binder.

[0025] Third, by comprehensively considering the agglomeration and buoyancy of the conductive agent and / or binder in the secondary battery electrode sheet, the reasons for achieving the desired distribution effect of the conductive agent and / or binder (agglomeration or buoyancy of the conductive agent and / or binder) can be determined. This provides a theoretical basis for adjusting the preparation process of the secondary battery electrode sheet, helping to obtain a secondary battery electrode sheet with a uniform distribution of conductive agent and / or binder, and optimizing the film resistance and other properties of the secondary battery electrode sheet. Measuring the distribution effect of the conductive agent and / or binder in the secondary battery electrode sheet using the method of this application can also evaluate the performance of the secondary battery, such as the film resistance performance of the secondary battery electrode sheet, providing theoretical support for the performance research and improvement of secondary batteries. Furthermore, it can determine whether the distribution effect of the conductive agent and / or binder in the secondary battery electrode sheet is qualified based on the film resistance requirements of different secondary batteries. Attached Figure Description

[0026] Figure 1 The image shows the SEM microstructure of the detection area of ​​the secondary battery electrode sheet obtained by the method in Example 1 of the specific implementation.

[0027] Figure 2 The image obtained by identifying and segmenting the components from the SEM microstructure image using the method of Example 1 in the specific implementation embodiment;

[0028] Figure 3 The threshold division map is obtained by the method of Example 1 in the specific implementation;

[0029] Figure 4 This is a line graph showing the content of conductive agent and binder in each layer obtained by the method in Example 1 of the specific implementation.

[0030] Figure 5The image shows the SEM microstructure of the detection area of ​​the secondary battery electrode sheet obtained by the method in Example 2 of the specific implementation.

[0031] Figure 6 The threshold division map is obtained by the method of Example 2 in the specific implementation;

[0032] Figure 7 This is a graph showing the area distribution data of the sample in Experimental Example 1 in the specific implementation method. Detailed Implementation

[0033] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0034] Example

[0035] The technical solution of this application will be described below with reference to specific embodiments. Unless otherwise specified, the raw materials used in the following embodiments are all from ordinary commercially available products, and the devices or equipment used are all purchased from conventional market sales channels.

[0036] Example 1

[0037] The method for determining the distribution of conductive agent and / or binder based on the morphology of secondary battery electrode sheets in this embodiment simultaneously detects both sides of a double-coated secondary battery electrode sheet, including the following steps:

[0038] Step S100: The secondary battery electrode sheet is cut along the thickness direction using an Ar ion beam cutter to create a cross-section. A detection area with a length of 2 mm and a width of 80 μm is selected from the electrode cross-section. SEM microstructure images are acquired segmentally using a field emission scanning electron microscope (FEI Apreo S) in 2 kV, 2 kX, T1 mode. Then, the acquired SEM microstructure images are stitched together using Maps automatic stitching software to form the SEM microstructure image of the detection area. The result is shown below. Figure 1 As shown.

[0039] Step S200: The image is processed using ImageJ image processing software. First, example labels for lithium cobalt oxide, conductive agent, binder, pores, and aluminum foil are manually added. Then, machine learning is used to automatically identify and segment lithium cobalt oxide, conductive agent, binder, pores, and aluminum foil from the SEM microstructure image. The segmented image is shown below. Figure 2 As shown. Figure 2Different colors represent different substances: purple represents lithium cobalt oxide, red represents conductive agents and binders, green represents voids, and yellow represents aluminum foil. The segmented images are saved and then imported into ImageJ.

[0040] The segmented image is processed into a grayscale image. Then, the grayscale image is thresholded from 0 to 131. Pixels with a grayscale value greater than or equal to 0 and less than 131 are assigned a grayscale value of 255, while pixels with a grayscale value greater than or equal to 131 are assigned a grayscale value of 0. Figure 3 The threshold division diagram is shown. Figure 3 In the diagram, the white parts represent conductive agents and binders, while the black parts represent other substances such as lithium cobalt oxide, voids, and aluminum foil. The conductive agents and binders are separated in the diagram by thresholding.

[0041] Step S300: Divide the detection area into upper and lower parts along the thickness direction of the secondary battery electrode sheet, using the aluminum foil current collector as the boundary. These are denoted as the upper electrode sheet and the lower electrode sheet, respectively. Layer the upper and lower electrode sheets along the electrode thickness direction, with each layer having a thickness of 2 μm. In the upper electrode sheet, n1 = 20, denoted as the 1st thickness layer, 2nd thickness layer, ..., 20th thickness layer; in the lower electrode sheet, n2 = 18, denoted as the 1st thickness layer, 2nd thickness layer, ..., 18th thickness layer, sequentially along the direction away from the current collector. Output the average grayscale data H of each thickness layer in the upper electrode sheet. i Determine the content of conductive agent and binder in each layer of the upper electrode. i1 =H i1 / 255, the area of ​​each thickness layer at the bottom of the electrode is 2×2000=4000μm. 2 According to w i2 =S i2 / S A2 The results of determining the content of conductive agent and binder in each layer of the lower part of the electrode are shown in Table 1 below. The results in Table 1 are statistically analyzed into a line graph as follows: Figure 4 As shown.

[0042] Table 1

[0043]

[0044]

[0045] Based on the requirements for the resistivity of the electrode film, the uniformity coefficient P = 1.5 is determined. From Table 1, it can be calculated that in the upper part of the electrode, w... q1 =∑w i1 / n1=9.05%, i1 takes values ​​in the range 1≤i1≤n1, P×(w q1 ) = 13.575%; in the lower part of the electrode, w q2 =∑w i2 / n2=8.57%, the range of i is 1≤i≤n, P×(w q2 = 12.86%. (Referring to Table 1 and...) Figure 4 Data shows that w in the upper part of the electrode i1 <13.575%, lower part of the electrode w i2 The percentage of conductive agent and binder in the upper and lower parts of the electrode sheet of the secondary battery is less than 12.86%, indicating that the distribution of conductive agent and binder in the upper and lower parts of the electrode sheet is uniform.

[0046] Calculate the buoyancy coefficients k1 and k2 for the upper and lower parts of the secondary battery electrode sheet based on the contents of conductive agent and binder in Table 1. In the upper part of the electrode sheet, w s1 w represents the average content of the detected substance in layers 1 through 10. s1 =∑w i / 10 = 8.57%, and the range of values ​​for i is 1 ≤ i ≤ 10; w x1 w represents the average content of the detected substance from the 11th to the 20th thickness layers. x1 =∑w i / 10 = 9.52%, the range of i is 11 ≤ i ≤ 20, k1 = w x1 / w s1 =9.52% / 8.57% = 1.11; in the lower part of the electrode, w s2 w represents the average content of the detected substance in layers 1 through 9. s2 =∑w i / 9 = 7.92%, and the range of values ​​for i is 1 ≤ i ≤ 9; w x2 w represents the average content of the detected substance from the 11th to the 20th thickness layers. x2 =∑w i / 10 = 9.21%, the range of values ​​for i is 10 ≤ i ≤ 18, k2 = w x2 / w s2 =9.21% / 7.92% = 1.16. Based on the internal resistance performance requirements of the secondary battery electrode sheet, the value of M is determined to be 2.0. This indicates that the conductive agent and binder in the secondary battery electrode sheet have not undergone significant upward floating, and their distribution effect can meet the internal resistance performance requirements of the secondary battery electrode sheet.

[0047] Example 2

[0048] The method for determining the distribution of conductive agent and / or binder based on the morphology of secondary battery electrode sheets in this embodiment includes the following steps:

[0049] Step S100: Select the detection area from the surface of the secondary battery electrode sheet, and use a field emission scanning electron microscope (model FEI Apreo S) in 10kV, 500X, T1 mode to continuously capture 15×15=225 SEM micro-morphology images using maps automatic stitching software and stitch them together to obtain the stitched SEM micro-morphology image as shown below. Figure 5 As shown.

[0050] Step S200: Process the image using ImageJ image processing software. First,... Figure 5 The image undergoes blurring and grayscale processing sequentially to obtain a grayscale image. Then, the grayscale image is divided into thresholds ranging from 0 to 41. Pixels with grayscale values ​​≥ 0 and < 41 are assigned a grayscale value of 0, while pixels with grayscale values ​​≥ 41 are assigned a grayscale value of 255. The resulting thresholded image is shown below. Figure 6 As shown, statistics Figure 6 The area distribution data of the detected substances (conductive agents and binders) are summarized into area intervals and corresponding quantity data due to space limitations. The results are shown in Table 2 below (the total area of ​​the interval in Table 2 is the total area of ​​the particles within the interval, and the total area of ​​the interval = the average value of the area interval × the number of particles. Taking the interval 0≤S<10 as an example, the total area of ​​the interval = ((0+10) / 2)*n).

[0051] Table 2

[0052]

[0053] S300. Based on the area distribution data in Table 2, the area for determining the critical value B of the large-area detection substance is 50 μm. 2 To obtain the degree of agglomeration of the secondary battery electrode sample, t = N B / N A =16050 / 3952750 = 0.406%, where N B For areas with an area ≥ 50 μm 2 The total area of ​​the conductive agent and the binder, N A This represents the total amount of conductive agent and binder distributed in the area distribution. Based on the required internal resistance performance of the secondary battery electrode sheet, T is set to 1%. Since the agglomeration degree of the secondary battery electrode sheet sample is t < T, it is determined that no agglomeration problem has occurred in the secondary battery electrode sheet sample.

[0054] Experimental Example 1

[0055] Three batches of secondary battery electrode samples were tested using the methods described in Examples 1 and 2. One sample was normal, while the other two samples experienced gelation issues in the ternary slurry during preparation, leading to electrode demolding during cold pressing. These three samples were designated as Normal, Abnormal-1, and Abnormal-2, respectively. The film resistance of the three electrodes was measured using a Yuaneng Technology BER1200 instrument. The film resistances obtained using the two-probe method were 1.68Ω, 3.30Ω, and 2.59Ω, respectively. The cause of the demolding problem was analyzed by examining the distribution of conductive agents and binders in the secondary battery electrodes.

[0056] The cross-section of the secondary battery electrode sheet sample cut along the thickness direction was tested using the method of Example 1, and the floating coefficient of each secondary battery electrode sheet sample was calculated: 1.9 for normal, 1.8 for abnormal-1, and 1.4 for abnormal-2.

[0057] The surface of the secondary battery electrode sheet was tested using the method in Example 2, and the area distribution data of the sample was obtained as follows: Figure 7 As shown ( Figure 7 The horizontal axis represents area, and the vertical axis represents the number of particles. Because the number of particles varies significantly across different areas... Figure 7 (The total number of substances detected in small areas is not shown). The number of particles in each area range obtained from the sample area distribution data is shown in Table 3 below.

[0058] Table 3

[0059] Area S interval Normal quantity Total area of ​​the interval Number of anomalies -1 Total area of ​​the interval Number of anomalies -2 Total area of ​​the interval 0≤S＜33 755903 12472399.5 583103 9621199.5 707150 11667975 33≤S＜66 735 36382.5 1641 81229.5 666 32967 66≤S＜99 51 4207.5 360 29700 75 6187.5 99≤S＜132 17 1963.5 127 14668.5 30 3465 132≤S＜165 1 148.5 29 4306.5 5 742.5 165≤S＜198 2 363 15 2722.5 3 544.5 198≤S＜231 1 214.5 12 2574 2 429 231≤S＜264 0 0 1 247.5 0 0

[0060] The area for determining the critical value B for large-area detection of substances is 66 μm. 2 ,according to Figure 7 The agglomeration degree t = N of the three secondary battery electrode samples was obtained from the area distribution data in Table 3. B / N A N B For areas with an area ≥ 66 μm 2 The total area of ​​the conductive agent and the binder, N A The area represents the total area of ​​the conductive agent and binder in the area distribution. The calculated aggregation degree t0 = 5.51% for the normal sample, t1 = 55.57% for the abnormal-1 sample, and t2 = 9.71% for the abnormal-2 sample.

[0061] The results of the above-mentioned floating degree and agglomeration degree show that the floating degree is: Normal > Abnormal-1 > Abnormal-2; the agglomeration degree is: Abnormal-1 > Abnormal-2 > Normal; and the membrane resistance is: Abnormal-1 > Abnormal-2 > Normal. It is evident that the agglomeration degree and membrane resistance follow the same pattern, indicating that in the three batches of secondary battery electrode samples tested in this experiment, the agglomeration of conductive agents and binders has a significant impact on their distribution, and is the main reason for slurry gelation and electrode demolding problems. Based on these test results, the preparation process of secondary battery electrode sheets can be improved to reduce or avoid the agglomeration problem of conductive agents and binders, thereby optimizing the membrane resistance and other properties of the secondary battery electrode sheets.

[0062] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for determining the distribution of conductive agent and / or binder based on the morphology of secondary battery electrode sheets, characterized in that, The method includes the following steps: Step S100: Select a detection area from the electrode sheet of the secondary battery and obtain a SEM microstructure image of the detection area; Step S200: Identify the detection substance in the SEM microstructure image; Step S300: Determine the distribution effect of the detection substance based on the area of ​​the detection substance; The detection substance is a conductive agent and / or a binder; The distribution effect includes the upward floating effect; When the detection area is a cross-section cut along the thickness direction of the secondary battery electrode sheet, in step S300, determining the distribution effect of the detection material based on the area of ​​the detection material includes: Step S301: Divide the detection area into n layers along the thickness direction of the secondary battery electrode sheet, and denoted as the 1st thickness layer, the 2nd thickness layer, ..., the nth thickness layer; the value of n is n≥2. Step S302: Determine the content w of the detection substance in each layer according to Formula II. i Based on the content w of the detected substance i To determine the buoyancy effect of conductive agents and / or binders; w i =S i / S A Formula II In Equation II, S i S is the area of ​​the detection material in the i-th thickness layer. A Let be the total area of ​​the i-th thickness layer, where i can take values ​​of 1 ≤ i ≤ n.

2. The method according to claim 1, characterized in that, The length of the detection area is L, and the value of L is in the range of 1 mm ≤ L ≤ 5 mm; The width of the detection area is W, and the value of W ranges from 40 μm to 1000 μm.

3. The method according to claim 1, characterized in that, Step S200 includes: The SEM microstructure image is sequentially processed for grayscale and thresholded to identify the detected substance.

4. The method according to claim 3, characterized in that, The method further includes at least one of the following conditions: Condition a: Before grayscale processing, the SEM microscopic morphology image is further subjected to blurring processing; Condition b: The threshold selection range for the threshold division is A~B, where the value range of A is 0≤A≤80, the value range of B is 40≤B≤200, and A<B.

5. The method according to claim 1, characterized in that, The detection area includes the surface of the secondary battery electrode sheet, and the distribution effect includes an aggregation effect. In step S300, determining the distribution effect of the detection substance based on its area includes: The area distribution of the detected substance is obtained based on its area, and the degree of aggregation t of the detection region is determined based on Equation I. t = N B / N A Formula I In formula I, N B N represents the total area of ​​the large-area detected substance in the detection region within the area distribution. A In the area distribution, the total area of ​​the detected substance in the detection region; The area of ​​the large-area detection substance is S', where S' ≥ h, and the value of h ranges from 50 to 300 μm. 2 ; If t≤T, then it is determined that the conductive agent and / or binder has not agglomerated; If t > T, then it is determined that the conductive agent and / or binder has agglomerated; The value of T is in the range of 0.1% ≤ T ≤ 10%.

6. The method according to claim 1, characterized in that, Step S302 further includes: The content of the detection substance w in each layer is determined according to Equation III. i Based on the content w of the detected substance i To determine the buoyancy effect of conductive agents and / or binders; w i =H i / 255 formula III In Equation III, H i Let be the average gray value of the detected material in the i-th thickness layer.

7. The method according to claim 1, characterized in that, The range of n is 2 ≤ n ≤ 40; and / or; The thickness of each layer is d, and the value of d ranges from 2 μm to 30 μm.

8. The method according to claim 1, characterized in that, The content of the detected substance w i To determine the buoyancy effect of conductive agents and / or binders, including: If w i ≤P×w q If the distribution is uniform, the conductive agent and / or binder are determined to be uniform; otherwise, the distribution is determined to be uneven. P is the uniformity coefficient, and the value of P ranges from 1.0 to 1.

5. w q w represents the average content of the detected substance from the 1st thickness layer to the nth thickness layer. q =∑w i / n.

9. The method according to claim 1, characterized in that, The content of the detected substance w i To determine the buoyancy effect of conductive agents and / or binders, including: According to equation IV, the buoyancy coefficient k is obtained; k = w x / w s Formula IV In equation IV, w s This represents the average content of the detected substance from the 1st thickness layer to the sth thickness layer, where s is an integer and n / 2 ≤ s < (n / 2 + 1), w s =∑w i / s, where the value of i ranges from 1 to i and from s to s; w x w represents the average content of the detected substance from the (s+1)th thickness layer to the nth thickness layer. x =∑w i / (ns), where the range of values ​​for i is s+1≤i≤n; The first thickness layer is the layer closest to the current collector; the nth thickness layer is the layer farthest from the current collector. If k≤M, then it is determined that the conductive agent and / or binder have not floated up; If k > M, then it is determined that the conductive agent and / or binder has floated up; The value of M is in the range of 1.0 ≤ M ≤ 2.0.

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