Method, device and equipment for detecting content of graphite secondary particles and medium

Abstract

The invention relates to the field of batteries, in particular to a method, device and equipment for detecting the content of graphite secondary particles and a medium. According to the method, the relation model is established according to the correlation between the overall isotropic degree of the graphite and the secondary particle content, so that the target secondary particle content of the target graphite can be directly determined according to the model, and the method is convenient to directly and quantitatively analyze the secondary particle content in the graphite.

Description

Technical Field

[0001] The present application relates to the field of batteries, and in particular to a method, device, equipment and medium for detecting the content of secondary graphite particles. Background Art

[0002] Secondary batteries are widely used in various consumer electronic products and electric vehicles due to their outstanding features such as light weight, no pollution, and no memory effect. Among them, lithium-ion batteries are widely used in portable electronic devices, electric vehicles and other fields.

[0003] As the application scope of secondary batteries becomes wider and wider, the requirements for battery performance are getting higher and higher. The negative electrode material is a key component of lithium-ion batteries. In lithium-ion batteries, the main carbon negative electrode material for large-scale application is graphite.

[0004] However, in the related art, there is no effective means to detect the secondary particle content of graphite. Summary of the invention

[0005] In view of the above problems, the present application provides a method, device, equipment and medium for detecting the content of secondary particles in graphite. The method is convenient for directly and quantitatively analyzing the content of secondary particles in graphite.

[0006] The first aspect of the present application is to provide a method for detecting the content of secondary graphite particles, the method comprising:

[0007] Obtaining OI values ​​of multiple graphite samples at different secondary particle contents;

[0008] Constructing a target correspondence model between the different secondary particle contents and the OI value;

[0009] The target secondary particle content of the target graphite is determined according to the target correspondence model.

[0010] The present application constructs a target correspondence model by combining the secondary particle contents of multiple graphite samples with the corresponding OI values. According to the target correspondence model, the target secondary particle content of the target graphite can be determined. This method is not only convenient for direct quantitative analysis of the secondary particle content in graphite, but also the error of the method itself is within a controllable range. In addition, this method can also conveniently guide the processing technology of secondary particles.

[0011] In some embodiments of the present application, obtaining OI values ​​of a plurality of graphite samples at different secondary particle contents comprises:

[0012] Providing a plurality of graphite samples, each of the graphite samples having a different secondary particle content;

[0013] Obtaining the secondary particle content and the corresponding OI value of each of the graphite samples;

[0014] The OI value obtained each time and the corresponding secondary particle content are stored to form a database.

[0015] In some embodiments of the present application, obtaining the secondary particle content and the corresponding OI value of each graphite sample includes:

[0016] The mass ratio of the secondary particles in each of the graphite samples is obtained as the secondary particle content;

[0017] The peak area of ​​the 004 crystal plane diffraction peak and the peak area of ​​the 110 crystal plane diffraction peak of each of the graphite samples are detected, and the ratio of the peak area of ​​the 004 crystal plane diffraction peak to the peak area of ​​the 110 crystal plane diffraction peak of each of the graphite samples is obtained as the OI value.

[0018] In some embodiments of the present application, constructing a target correspondence model of different secondary particle contents and the OI value includes:

[0019] The OI values ​​under the different secondary particle contents are used to fit the linear relationship between the secondary particle content and the OI value as a target corresponding model.

[0020] In some embodiments of the present application, the fitting of the linear relationship between the secondary particle content and the OI value as a target correspondence model comprises:

[0021] Performing linear regression processing on the secondary particle content and the OI value to obtain a preset corresponding model;

[0022] Determining whether the preset corresponding model meets the preset accuracy condition;

[0023] If they match, the preset corresponding model is determined as the target corresponding model;

[0024] If not, a new linear regression process is performed on the secondary particle content and the OI value until the preset accuracy condition is met.

[0025] In some implementations of the present application, the determining whether the preset corresponding model meets the preset accuracy condition includes:

[0026] Determining the theoretical content of the secondary particles according to the preset corresponding model;

[0027] Obtaining the actual content of the secondary particles;

[0028] determining the difference between the theoretical content and the actual content of the secondary particles,

[0029] According to the difference between the theoretical content and the actual content of the secondary particles exceeding a threshold value, determining that the preset corresponding model does not meet the preset accuracy condition;

[0030] According to the fact that the difference between the theoretical content and the actual content of the secondary particles does not exceed a threshold value, it is determined that the preset corresponding model meets the preset accuracy condition.

[0031] In some embodiments of the present application, determining the target secondary particle content of the target graphite according to the target correspondence model includes:

[0032] The target OI value of the target graphite is input into the target corresponding model, and the target secondary particle content is output.

[0033] In some embodiments of the present application, the secondary particle content of the graphite sample is greater than zero and less than or equal to 100%, preferably 25% to 100%.

[0034] A second aspect of the present application is to provide a device for detecting the content of secondary graphite particles, the device comprising:

[0035] Data acquisition module: used to obtain OI values ​​of multiple graphite samples at different secondary particle contents;

[0036] A construction module; used to construct a target correspondence model between the different secondary particle contents and the OI value;

[0037] Output module: used to output the target secondary particle content of the target graphite.

[0038] The third aspect of the present application is to provide an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method described in the first aspect when executing the computer program.

[0039] The fourth aspect of the present application is to provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the method described in the first aspect when executed by a processor.

[0040] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present application. Moreover, the same reference numerals are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0042] Figure 1A Schematic diagram of the microstructure of graphite primary particles according to some embodiments of the present application.

[0043] Figure 1B This is a schematic diagram of the structure of stacked graphite primary particles in some embodiments of the present application.

[0044] Figure 2A Schematic diagram of the microstructure of graphite secondary particles according to some embodiments of the present application.

[0045] Figure 2B This is a schematic diagram of the structure of stacked graphite secondary particles in some embodiments of the present application.

[0046] Figure 3 A flow chart of a detection method according to some embodiments of the present application;

[0047] Figure 4 Schematic diagram of the structure of different crystal planes of graphite in some embodiments of the present application.

[0048] Figure 5 A flow chart of a detection method according to some embodiments of the present application;

[0049] Figure 6 A flow chart of a detection method according to some embodiments of the present application;

[0050] Figure 7 A flow chart of a detection method according to some embodiments of the present application;

[0051] Figure 8 A flow chart of a detection method according to some embodiments of the present application;

[0052] Fig. 9 A flow chart of a detection method according to some embodiments of the present application;

[0053] Fig.10 A linear relationship diagram between the OI value and the corresponding secondary particle content of some embodiments of the present application;

[0054] Fig.11 A schematic diagram of a detection device according to some embodiments of the present application;

[0055] Fig.12 This is a schematic diagram of the device structure of some embodiments of the present application.

[0056] The numbers in the attached drawings are as follows:

[0057] 400, data acquisition module; 500, construction module; 600, output module; 700, communication interface; 800, processor; 900, memory; 1000, bus. DETAILED DESCRIPTION

[0058] The following embodiments of the technical solution of the present application are described in detail in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present application, and are therefore only used as examples, and cannot be used to limit the scope of protection of the present application.

[0059] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by technicians in the technical field to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" in the specification and claims of this application and the above-mentioned figure descriptions and any variations thereof are intended to cover non-exclusive inclusions.

[0060] In the description of the embodiments of the present application, the technical terms "first", "second", etc. are only used to distinguish different objects, and cannot be understood as indicating or implying relative importance or implicitly indicating the number, specific order or primary and secondary relationship of the indicated technical features. In the description of the embodiments of the present application, the meaning of "multiple" is more than two, unless otherwise clearly and specifically defined.

[0061] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0062] In the description of the embodiments of the present application, the term "and / or" is only a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists, A and B exist at the same time, and B exists. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0063] In the description of the embodiments of the present application, the term "multiple" refers to more than two (including two). Similarly, "multiple groups" refers to more than two groups (including two groups), and "multiple pieces" refers to more than two pieces (including two pieces).

[0064] For those of ordinary skill in the art, the specific meanings of the above terms in the embodiments of the present application can be understood according to specific circumstances.

[0065] At present, the carbon negative electrode materials that have been applied on a large scale in lithium-ion batteries are mainly natural graphite and artificial graphite. In the domestic battery system, artificial graphite has better performance than natural graphite and is widely used as negative electrode material for lithium-ion batteries.

[0066] Common artificial graphite materials mainly have secondary particle structure, single particle structure or a structure formed by a mixture of single particle and secondary particle structure. Compared with artificial graphite materials with single particle structure of the same particle size distribution, artificial graphite with secondary particle structure has excellent rate performance and high compaction density, and has always been favored by customers. Research has also found that after secondary granulation of single graphite particles, Li + The number of channels for embedding and de-embedding in the lattice further improves the rate performance and low-temperature performance of the negative electrode material.

[0067] However, there is currently no effective means to detect the content of secondary particles in artificial graphite. The method of simply taking SEM photos and artificially counting particles is prone to large errors and cannot be used for quantitative analysis.

[0068] Since the physical properties of the same substance in all directions are the same, that is, they are independent of orientation, they are isotropic; if the physical properties in all directions are different and are related to orientation, they are anisotropic. The single-particle structure of graphite is anisotropic, while the secondary particle structure is isotropic. The particle structure of graphite can be qualitatively tested based on the difference in the physical properties. If the graphite particle structure with different physical properties can be linked to the content, it will be helpful to improve the detection method of the secondary particle structure of graphite.

[0069] Based on the above considerations, in order to solve the problem that there is currently no effective means to detect the secondary particle content of graphite, relevant experimental research was carried out according to the above design concept to obtain a detection method for the secondary particle content of graphite. The secondary particle content of multiple graphite samples obtained is linked to their physical property structure and constructed to form a target correspondence model. According to the target correspondence model, the target secondary particle content of the target graphite can be determined.

[0070] like Figure 1A , 1B, 2A and 2B show that the primary graphite particles are layered single crystals, the atoms within the layers are bonded by strong covalent bonds, and the atoms between the layers are bonded by van der Waals bonds. Therefore, the properties of the crystal layer direction and the direction perpendicular to the layer direction are quite different, showing anisotropy. The secondary graphite particles are composed of a plurality of graphite single crystals arranged in an disordered orientation, and are spherical structures, so they are isotropic as a whole. And experimental research has found that the secondary particle content is strongly correlated with the overall isotropy of the material. The present application establishes a relationship model based on the correlation between the overall isotropy of graphite and the secondary particle content, and then the target secondary particle content of the target graphite can be directly determined based on the model. This method is not only convenient for direct quantitative analysis of the secondary particle content in graphite, but also the error of the method itself is within a controllable range. In addition, this method can also conveniently guide the processing technology of secondary particles.

[0071] In this application Figure 1A , Figure 2A The single and secondary particles of graphite were obtained by scanning the SEM scanning electron microscope of ThermoFisher, among which, Figure 1A The detection conditions are: EHT = 10.00 kV, signal A = lnLens, WD = 4.4 mm, Mag = 5.00 KX; Figure 2A The detection conditions are: EHT=10.00kV, signal A=lnLens, WD=4.4mm, Mag=2.00KX.

[0072] The method for detecting the content of secondary graphite particles disclosed in the embodiments of the present application can be used, but is not limited to, in the preparation process of negative electrode plates and the production process of secondary batteries, and can also be used in the production processes of other similar structures.

[0073] In some embodiments of the present application, the secondary battery can be used in electrical equipment, including but not limited to electronic equipment, electric toys, electric tools, battery cars, electric cars, ships, spacecraft, etc. Among them, electronic equipment includes but is not limited to various personal computers, laptops, smart phones and tablet computers. Electric toys can include fixed or mobile electric toys, such as electric car toys, electric ship toys and electric airplane toys, etc., and spacecraft can include airplanes, rockets, space shuttles and spacecrafts, etc.

[0074] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0075] In some embodiments of the present application, Figure 3This is a flow chart of a method for detecting the content of secondary graphite particles in some embodiments of the present application. The method for detecting the content of secondary graphite particles comprises the following steps:

[0076] Step S100, obtaining OI values ​​of a plurality of graphite samples at different secondary particle contents;

[0077] Step S200, constructing a target correspondence model between different secondary particle contents and OI values;

[0078] Step S300: determining a target secondary particle content of target graphite according to a target corresponding model.

[0079] The graphite sample in this application is artificial graphite, which contains single graphite particles and secondary graphite particles. Based on the total weight of the artificial graphite, the mass percentage content of the secondary graphite particles is 0-100%. The OI value of the graphite sample is the graphite orientation degree, such as Figure 4 Schematically, the plane where the coordinate axes X and Y directions are located is the plane where the graphite layered structure is located, and the coordinate axis Z direction is perpendicular to the plane. The graphite orientation degree is the ratio of the peak integral area of ​​the 004 / 110 crystal plane peak, which can be used to characterize the overall isotropy degree of graphite. Generally, the smaller the OI value, the better the isotropy. And the peak integral area of ​​the 004 crystal plane peak and the peak integral area of ​​the 110 crystal plane peak are measured using conventional measuring instruments in the art, such as X-ray diffractometers.

[0080] The target graphite in the present application includes graphite that needs to be detected according to the detection method of the present application, and can also be other materials such as pole pieces containing graphite.

[0081] The present application establishes a target correspondence model based on the different contents of secondary particles in multiple graphite samples and the corresponding OI values. The target correspondence model directly links the secondary particle content with the OI value. Based on the target correspondence model and after the OI value of the target graphite is determined, the target correspondence model can be used to directly obtain the secondary particle content of the graphite. Therefore, the method designed in the present application is convenient for direct quantitative analysis of the secondary particle content of graphite.

[0082] In some embodiments of the present application, step S100 includes: Figure 5 Illustrated steps:

[0083] Step S110, providing a plurality of graphite samples, each graphite sample having a different secondary particle content;

[0084] Step S120, obtaining the secondary particle content and the corresponding OI value of each graphite sample;

[0085] Step S130: storing the OI value and the corresponding secondary particle content obtained each time to form a database.

[0086] The present application establishes a database from a statistical point of view by obtaining the secondary particle content of multiple graphite samples and the OI values ​​at different secondary particle contents. The database is helpful in guiding the construction of a target correspondence model.

[0087] In some embodiments of the present application, step S120 includes: Figure 6 Illustrated steps:

[0088] Step S121, obtaining the mass ratio of secondary particles in each graphite sample as the secondary particle content;

[0089] Step S122, detecting the peak area of ​​the 004 crystal plane diffraction peak and the peak area of ​​the 110 crystal plane diffraction peak of each graphite sample, and obtaining the ratio of the peak area of ​​the 004 crystal plane diffraction peak to the peak area of ​​the 110 crystal plane diffraction peak of each graphite sample as the OI value.

[0090] In the present application, the secondary particle content of each selected graphite sample is determined, such as a graphite sample provided by a supplier or a sample formed by mixing a single graphite particle with secondary particles according to a certain content. The peak area of ​​the 004 crystal plane diffraction peak and the peak area of ​​the 110 crystal plane diffraction peak of each graphite sample are obtained by directly measuring using any conventional detection instrument in the art, such as XRD.

[0091] In some embodiments of the present application, step S200 includes: Figure 7 Illustrated steps:

[0092] Step S210: using the OI values ​​at different secondary particle contents, fitting the linear relationship between the secondary particle content and the OI value as a target corresponding model.

[0093] In the present application, based on the correlation between the overall isotropy of graphite and the secondary particle content, the linear relationship between the secondary particle content of graphite and the OI value can be fitted by the following formula (1).

[0094] Y=k×a+b formula (1).

[0095] In formula (1), Y represents the OI value of a graphite sample, a represents the secondary particle content of the same graphite sample, k represents the slope parameter, and b represents the intercept parameter.

[0096] The present application may use formula (1) or other modified or equivalent formulas to fit the secondary particle content of graphite and the OI value, which is not limited in the embodiments of the present application.

[0097] The present application can directly characterize the secondary particle content of graphite according to the above formula (1).

[0098] In some embodiments of the present application, step S210 includes: Figure 8 Illustrated steps:

[0099] Step S211, performing linear regression processing on the secondary particle content and the OI value to obtain a preset corresponding model;

[0100] Step S212: Determine whether the preset corresponding model meets the preset accuracy condition:

[0101] If they match, the pre-set corresponding model is determined as the target corresponding model;

[0102] If not, a new linear regression process is performed on the secondary particle content and OI value until the preset accuracy conditions are met.

[0103] Based on the established database, the present application sets the formula (1) obtained by fitting the secondary particle content and the OI value as a pre-set corresponding model. In order to detect the accuracy of the pre-set corresponding model, it is also necessary to determine whether the pre-set corresponding model meets the preset accuracy conditions. If it meets the preset accuracy conditions, the pre-set corresponding model is determined as the target corresponding model; if it does not meet the preset accuracy conditions, the database can be expanded and a new linear regression processing can be performed on the secondary particle content and the OI value until formula (2) is obtained: Y'=k'×a'+b' formula (2).

[0104] In formula (2), Y' represents the corrected OI value of a graphite sample, a' represents the corrected secondary particle content of the same graphite sample, k' represents the corrected slope parameter, and b' represents the corrected intercept parameter.

[0105] The formula (2) meets the preset accuracy condition and can be used as the target corresponding model. If the formula (2) still does not meet the preset accuracy condition, the above method is used to repeat the correction until the preset accuracy condition is met.

[0106] In some embodiments of the present application, the process of determining whether a preset corresponding model meets a preset accuracy condition includes the following steps:

[0107] Step (1), determining the theoretical content of secondary particles according to a preset corresponding model;

[0108] Step (2), obtaining the actual content of secondary particles;

[0109] Step (3), determining the difference between the theoretical content and the actual content of the secondary particles,

[0110] Step (4), determining that the preset corresponding model does not meet the preset accuracy condition according to the difference between the theoretical content and the actual content of the secondary particles exceeding the threshold value;

[0111] Step (5), determining that the preset corresponding model meets the preset accuracy condition based on the difference between the theoretical content and the actual content of the secondary particles not exceeding the threshold.

[0112] In the present application, the actual content of the secondary particles can be provided by the supplier, or directly calculated when the composition and content are known. At the same time, the threshold is used to determine the preset accuracy, and the method for determining the threshold includes obtaining it by using a statistical method.

[0113] In some embodiments of the present application, the method for detecting the content of secondary graphite particles is as follows: Fig. 9 The schematic includes the following steps:

[0114] Step 1: The process of obtaining data including secondary particle contents and corresponding OI values ​​of multiple graphite samples.

[0115] Step 2: The process of fitting the content of each secondary particle and the corresponding OI value and establishing a linear relationship.

[0116] Step 3: Assign the secondary particle content a1.

[0117] Step 4: Determine whether (a-a1)≤±m holds.

[0118] Step 5: The linear relationship Y is established.

[0119] Step 6: Not true, refit the secondary particle contents and corresponding OI values ​​to obtain the linear relationship Y'.

[0120] Step 7: Replace the linear relationship Y with Y'.

[0121] Step 8: Input the target OI value of the target graphite and output the target secondary particle content.

[0122] The m value in this application is the threshold value.

[0123] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0124] For ease of understanding, the following embodiments of the present application will introduce the method for determining the secondary particle content using graphite powder as an example.

[0125] Wherein, the graphite powder is a mixture of single particles and secondary particles of graphite, wherein the single particles and secondary particles of graphite are needle coke made by conventional artificial graphite process in the art, the needle coke includes any conventional model in the art, and the single particles of graphite have no granulation process, and the secondary particles have a granulation process. The granulation process in this field includes any conventional process in this field. In some embodiments of the present application, the secondary particles of graphite are based on small-particle needle coke, asphalt is used as a binder, and the temperature is raised in the reactor, and the binder is softened, melted, and coked at a temperature of about 500 to 1000°C, thereby converting the primary particles of graphite into secondary particles. The asphalt used in this application includes any conventional model in the art. The granulation process involved in this application, such as softening, melting, coking, etc., includes any conventional process parameters in the art.

[0126] Step 1): Weigh 10g, 8g, 6g, 4g, 2g and 0g of single graphite particles respectively, and mix them evenly with 0g, 2g, 4g, 6g, 8g and 10g of secondary graphite particles respectively to obtain 6 graphite samples, and calculate the secondary particle content in each sample as shown in Table 1.

[0127] Step 2): Use a Bruker D8 DISCOVER x-ray diffractometer to detect the peak area of ​​the diffraction peak of the 004 crystal plane and the peak area of ​​the diffraction peak of the 110 crystal plane of each sample in step 1), and calculate the OI value of each graphite sample = C004 / C110. The OI value of each sample is shown in Table 1.

[0128] Table 1 List of graphite samples

[0129]

[0130]

[0131] Step 3): With the OI value as the ordinate and the secondary particle content as the abscissa, the secondary particle content of each sample is fitted with the OI value on the coordinate axis. The fitted curve is as follows: Fig.10 As shown, the linear relationship of the curve is established, and Y=-3.8153x+7.0747 is obtained.

[0132] Step 4): Four graphite samples were obtained by the methods of step 1) and step 2). The secondary particle content of the four graphite samples was between 0% and 40%. The OI values ​​of the four graphite samples were shown in Table 2.

[0133] Step 5): Substitute the OI values ​​of the three graphite samples into the curve established in step 3) to obtain the theoretical content of each graphite sample, as shown in Table 2.

[0134] Table 2 List of graphite samples

[0135]

[0136] Combined with Table 2, it can be seen that the difference between the theoretical content and the actual content of secondary particles in four of the graphite samples does not exceed the threshold, which proves that the accuracy of the linear relationship established in step 3) is high. If the difference of more than half of the samples exceeds the threshold, a new linear regression process is required for the secondary particle content and the OI value until most of the differences in the samples do not exceed the threshold.

[0137] It can be seen that the detection method designed in the present application can determine the target secondary particle content of the target graphite according to the target corresponding model. This method is convenient for direct quantitative analysis of the secondary particle content in the graphite, and is affected by the uniformity of the graphite secondary particles. The error of the method designed in the present application itself is within a controllable range.

[0138] Combining Table 1 and Table 2, it can be seen that as the secondary particle content in graphite increases, the difference between the actual value and the theoretical value obtained using the above linear relationship also decreases. Therefore, the detection method for the secondary particle content of graphite described in this application is applicable to graphite secondary particle content greater than or equal to 25%.

[0139] In addition, since the preparation process of graphite secondary particles is relatively complicated, the entire preparation process is usually an intermittent unit operation. If the detection method of the present application is used to directly and quantitatively analyze the secondary particle content in the graphite, it will be beneficial for guiding the processing technology of the secondary particles.

[0140] Based on the same inventive concept, in some embodiments of the present application, the present application also discloses a device for realizing the above-mentioned determination of secondary particle content. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above-mentioned method, so the specific limitations in one or more embodiments of the device for determining the secondary particle content provided below can refer to the limitations of the secondary particle content determination method above, and will not be repeated here.

[0141] In some embodiments of the present application, Fig.11 Schematic diagram of the structure of the device for measuring the secondary particle content in some embodiments of the present application. The device for measuring the secondary particle content provided in the embodiments of the present application can be applied to electronic devices. Fig.11 As shown, the device of the embodiment of the present application may include: a data acquisition module, a construction module and an output module.

[0142] In some embodiments of the present application, the data acquisition module is used to obtain OI values ​​of a plurality of graphite samples at different secondary particle contents.

[0143] In some embodiments of the present application, the construction module is used to construct a target correspondence model between the different secondary particle contents and the OI value.

[0144] In some embodiments of the present application, the output module is used to output a target secondary particle content of the target graphite.

[0145] In some embodiments of the present application, Fig.12 is a schematic diagram of the structure of an electronic device according to an embodiment of the present application, such as Fig.12 As shown, the electronic device provided in the embodiment of the present application may include a processor, a memory and a communication interface connected by a system bus. Among them, the processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the electronic device is used to communicate with an external terminal in a wired or wireless manner. When the computer program is executed by the processor to implement the technical solution in the embodiment of the detection method of the graphite secondary particle content of the above-mentioned graphite secondary particle content detection method of the present application, its implementation principle and technical effect are similar, and will not be repeated here.

[0146] Those skilled in the art will understand that Fig.12 The structure shown in the figure is merely a block diagram of a partial structure related to the scheme of the present application, and does not constitute a limitation on the electronic device to which the scheme of the present application is applied. The specific electronic device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0147] In some embodiments, an electronic device is also provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the technical solution in the above-mentioned method for detecting the content of secondary graphite particles in the present application is implemented. The implementation principle and technical effect are similar and will not be repeated here.

[0148] In some embodiments, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the technical solution of the method for detecting the content of secondary graphite particles mentioned above in the present application is implemented. The implementation principle and technical effect are similar and will not be repeated here.

[0149] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The processor involved in each embodiment provided in this application can be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, etc., but is not limited thereto.

[0150] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application, and they should all be included in the scope of the claims and specification of the present application. In particular, as long as there is no structural conflict, the various technical features mentioned in the various embodiments can be combined in any way. The present application is not limited to the specific embodiments disclosed herein, but includes all technical solutions that fall within the scope of the claims.

Claims

1. A method for detecting the content of secondary graphite particles, characterized in that: The method comprises: Obtaining OI values ​​of multiple graphite samples at different secondary particle contents; Constructing a target correspondence model between the different secondary particle contents and the OI value; The target secondary particle content of the target graphite is determined according to the target correspondence model.

2. The method according to claim 1, characterized in that The obtaining of OI values ​​of a plurality of graphite samples at different secondary particle contents comprises: Providing a plurality of graphite samples, each of the graphite samples having a different secondary particle content; Obtaining the secondary particle content and the corresponding OI value of each of the graphite samples; The OI value obtained each time and the corresponding secondary particle content are stored to form a database.

3. The method according to claim 2, characterized in that The obtaining of the secondary particle content and the corresponding OI value of each graphite sample comprises: The mass ratio of the secondary particles in each of the graphite samples is obtained as the secondary particle content; The peak area of ​​the 004 crystal plane diffraction peak and the peak area of ​​the 110 crystal plane diffraction peak of each of the graphite samples are detected, and the ratio of the peak area of ​​the 004 crystal plane diffraction peak to the peak area of ​​the 110 crystal plane diffraction peak of each of the graphite samples is obtained as the OI value.

4. The method according to claim 1, 2 or 3, characterized in that: The constructing of the target correspondence model between the different secondary particle contents and the OI value comprises: The OI values ​​under the different secondary particle contents are used to fit the linear relationship between the secondary particle content and the OI value as a target corresponding model.

5. The method according to claim 4, characterized in that The fitting of the linear relationship between the secondary particle content and the OI value as a target corresponding model includes: Performing linear regression processing on the secondary particle content and the OI value to obtain a preset corresponding model; Determining whether the preset corresponding model meets the preset accuracy condition; If they match, the preset corresponding model is determined as the target corresponding model; If not, a new linear regression process is performed on the secondary particle content and the OI value until the preset accuracy condition is met.

6. The method according to claim 5, characterized in that The determining whether the preset corresponding model meets the preset accuracy condition includes: Determining the theoretical content of the secondary particles according to the preset corresponding model; Obtaining the actual content of the secondary particles; Determining the difference between the theoretical content and the actual content of the secondary particles; According to the difference between the theoretical content and the actual content of the secondary particles exceeding a threshold value, determining that the preset corresponding model does not meet the preset accuracy condition; According to the fact that the difference between the theoretical content and the actual content of the secondary particles does not exceed a threshold value, it is determined that the preset corresponding model meets the preset accuracy condition.

7. The method according to claim 1 or 2 or 3 or 5 or 6, characterized in that: Determining the target secondary particle content of the target graphite according to the target corresponding model includes: The target OI value of the target graphite is input into the target corresponding model, and the target secondary particle content is output.

8. The method according to claim 1 or 2 or 3 or 5 or 6, characterized in that: The secondary particle content of the graphite sample is greater than zero and less than or equal to 100%, preferably 25% to 100%.

9. A device for detecting the content of secondary graphite particles, characterized in that: The device comprises: Data acquisition module: used to obtain OI values ​​of multiple graphite samples at different secondary particle contents; A construction module; used to construct a target correspondence model between the different secondary particle contents and the OI value; Output module: used to output the target secondary particle content of the target graphite.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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