Inspection method for cathode active material, and manufacturing method of non-aqueous electrolyte secondary battery

Abstract

To provide an inspection method for a cathode active material capable of obtaining information relating to a state after a non-aqueous electrolyte secondary battery is charged / discharged without performing a test in which the non-aqueous electrolyte secondary battery is actually charged / discharged.SOLUTION: A part of a cathode active material, which is composed in a composition step (S10), is subjected to XRD measurement as a specimen (S12). Based on a measurement result, Rietveld analysis is applied by a PU. The PU then creates a crystal structure model of the specimen based on an analysis result. Next, the PU sets a temperature T. The PU then inputs the temperature and the created model to a machine learning field, thereby predicting a diffusion of a transition metal (S22). In a case where a temperature T(n-1) which is an upper limit where the transition metal is determined not to be diffused is equal to or higher than a threshold Tth, the PU determines the inspection as a success.SELECTED DRAWING: Figure 4

Description

Technical Field

[0001] The present invention relates to a method for inspecting a positive electrode active material and a method for manufacturing a non-aqueous electrolyte secondary battery.

Background Art

[0002] The following Patent Document 1 describes a method for manufacturing a lithium nickel-containing composite oxide used in a lithium ion secondary battery. This manufacturing method suppresses the occurrence of cation mixing by setting the lithium nickel-containing composite oxide to 800°C or lower. Further, the same document also describes detecting cation mixing in the lithium nickel-containing composite oxide by Rietveld analysis of X-ray diffraction.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] By the way, when cation mixing occurs with the use of a lithium ion secondary battery, the lithium ion secondary battery deteriorates. In order to grasp in advance the deterioration due to the use of a lithium ion secondary battery, when conducting a test to evaluate the deterioration by charging and discharging a manufactured test lithium ion secondary battery, the man-hours required for the test increase.

Means for Solving the Problems

[0005] Hereinafter, means for solving the above problems and their operational effects will be described. 1. A method for inspecting a positive electrode active material constituting a non-aqueous electrolyte secondary battery, the method comprising an acquisition step, a prediction step, and an evaluation step, wherein the acquisition step is a step of acquiring crystal structure information of the synthesized positive electrode active material, the crystal structure information includes a ratio of cation mixing, the prediction step is a step of predicting diffusion of a transition metal constituting the positive electrode active material by computer-aided molecular dynamics calculation according to the crystal structure information, and the evaluation step is a step of evaluating the quality of the positive electrode active material according to the result of the prediction step.

[0006] In the above method, by predicting the diffusion of the transition metal due to the use of the non-aqueous electrolyte secondary battery, it is possible to predict whether cation mixing occurs due to use. Therefore, information regarding the state after charging and discharging the non-aqueous electrolyte secondary battery can be obtained without actually performing a test of charging and discharging the non-aqueous electrolyte secondary battery.

[0007] Incidentally, the accuracy of this prediction depends on the accuracy of the crystal structure information. Here, during the production of the positive electrode active material, cation mixing can occur to some extent. Therefore, in the above method, the prediction step is executed using crystal structure information including information regarding the ratio of cation mixing. Thereby, the prediction accuracy of diffusion can be increased. Therefore, in the above method, the accuracy of the evaluation result in the evaluation step can be increased.

[0008] 2. The method for inspecting a positive electrode active material according to the above 1, wherein the prediction step is a step of predicting, by the computer, diffusion of the transition metal for each case where the temperature of the positive electrode active material is set variously, and the evaluation step includes a step of evaluating that the quality of the positive electrode active material meets the requirements when an upper limit value of a temperature at which the transition metal does not diffuse among the results of the prediction step is equal to or higher than a threshold value.

[0009] When predicting the state of the positive electrode active material at the time when only the required usage time of the non-aqueous electrolyte secondary battery has elapsed, the computational load tends to increase. On the other hand, the state when the non-aqueous electrolyte secondary battery is used for a long time can be approximately represented by the state when the non-aqueous electrolyte secondary battery is in a high-temperature state. Therefore, in the above method, the diffusion of the transition metal is predicted when the temperature of the positive electrode active material is set variously. Thereby, the usage time when the transition metal starts to diffuse can be grasped according to the temperature at which the transition metal diffuses. Therefore, the prediction process for evaluating whether the positive electrode active material can satisfy the quality over the required usage time can be executed without excessively increasing the computational load.

[0010] 3. The prediction step is the step of predicting, by a computer, the diffusion of the transition metal in a state where the charge rate of the non-aqueous electrolyte secondary battery is equal to or higher than a predetermined value, according to the method for inspecting a positive electrode active material described in 1 or 2 above.

[0011] When the charge rate is high, the deterioration rate of the positive electrode active material is higher than when the charge rate is low. Therefore, in the above method, by predicting the diffusion of the transition metal in a state where the charge rate is equal to or higher than a predetermined value, the timing for predicting whether the transition metal diffuses can be set to a time after a shorter period of time compared to the case where the charge rate is less than the predetermined value.

[0012] 4. The acquisition step includes a process of calculating the ratio of cation mixing by Rietveld analysis of the positive electrode active material, according to the method for inspecting a positive electrode active material described in any one of 1 to 3 above. In the above method, the ratio of cation mixing can be calculated using simpler equipment than when performing STEM observation or the like.

[0013] 5. The prediction step includes a step of predicting, by a computer, the time change of the coordinates of the transition metal by inputting a crystal structure model of the positive electrode active material into a learned model, according to the method for inspecting a positive electrode active material described in any one of 1 to 4 above.

[0014] In the above method, by using a learned model, it is possible to achieve a suitable compromise between calculating the time change of the coordinates of the transition metal with high accuracy and calculating without increasing the computational load.

[0015] 6. A method for manufacturing a non-aqueous electrolyte secondary battery, comprising: a synthesis step of synthesizing a positive electrode active material constituting the non-aqueous electrolyte secondary battery; the acquisition step, the prediction step, and the evaluation step in the inspection method of the positive electrode active material according to any one of 1 to 5 above; and a feedback step of feeding back the result of the evaluation step to the synthesis step when the quality of the positive electrode active material is not evaluated to meet the requirements by the evaluation step.

[0016] In the above configuration, by making the positive electrode active material synthesized in the manufacturing process of the non-aqueous electrolyte secondary battery the object of evaluation by the evaluation step, the synthesis step can be evaluated. Therefore, when a change occurs in the quality of the positive electrode active material generated by the synthesis step during mass production of the non-aqueous electrolyte secondary battery, the synthesis step can be corrected.

Brief Description of the Drawings

[0017]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Embodiments for Carrying Out the Invention

[0018] Hereinafter, an embodiment will be described with reference to the drawings. "Premise Configuration" FIG. 1 is a perspective view showing an outline of the configuration of the lithium-ion secondary battery 1 of the present embodiment. The lithium-ion secondary battery 1 shown in FIG. 1 is a battery cell that constitutes an in-vehicle battery pack. The lithium-ion secondary battery 1 includes a rectangular parallelepiped-shaped battery case 11 having an opening on the upper side. An electrode body 12 is housed inside the battery case 11. The battery case 11 is filled with a non-aqueous electrolyte 13 from a liquid injection hole. The battery case 11 is made of a metal such as an aluminum alloy, and forms a sealed battery container. The lithium-ion secondary battery 1 also includes a positive electrode external terminal 14 and a negative electrode external terminal 15 used for charging and discharging electric power. The positive electrode external terminal 14 is electrically connected to a positive electrode current collector terminal 16 inside the battery case 11. Also, the negative electrode external terminal 15 is electrically connected to a negative electrode current collector terminal 17 inside the battery case 11. Note that the shapes of the positive electrode external terminal 14 and the negative electrode external terminal 15 are not limited to those shown in FIG. 1.

[0019] The non-aqueous electrolyte 13 is filled in the battery container formed by the battery case 11. The non-aqueous electrolyte 13 of the lithium-ion secondary battery 1 is a composition in which a lithium salt is dissolved in an organic solvent. As the lithium salt, LiClO 4 , LiPF 6 , LiAsF 6 , LiBF 4 , LiSO 3 CF 3 etc. can be used. Examples of the organic solvent include cyclic carbonates, ether compounds, and phosphorus compounds. As the non-aqueous electrolyte, these can be used by mixing one or more types thereof. The composition of the non-aqueous electrolyte 13 is not limited to this.

[0020] FIG. 2 is a schematic diagram showing the configuration of the wound electrode body 12. The electrode body 12 of the lithium ion secondary battery 1 includes a negative electrode plate 2, a positive electrode plate 3, and a separator 4. Specifically, the electrode body 12 is formed by flatly winding a large number of negative electrode plates 2, positive electrode plates 3, and a separator 4 disposed therebetween. The negative electrode plate 2 has a negative electrode composite material layer 22 formed on a negative electrode current collector 21 serving as a base material. A negative electrode connection portion 23 where the negative electrode composite material layer 22 is not formed and the negative electrode current collector 21 is exposed is provided on one end side in the width direction W (winding axis direction) orthogonal to the winding direction L. The negative electrode connection portion 23 is electrically connected to the negative electrode current collecting terminal 17.

[0021] The negative electrode plate 2 has negative electrode composite material layers 22 on both sides of a negative electrode current collector 21 serving as a negative electrode base material. The negative electrode current collector 21 is composed of, for example, a Cu foil. The negative electrode current collector 21 serves as a base as an aggregate of the negative electrode composite material layer 22 and has a function of a current collecting member for collecting electricity from the negative electrode composite material layer 22. The negative electrode composite material layer 22 is produced, for example, by kneading a negative electrode active material, a solvent, and a binder, and applying and drying the kneaded negative electrode composite material paste on the negative electrode current collector 21. The negative electrode active material is a material capable of occluding and releasing lithium ions. The negative electrode active material is, for example, a powdery carbon material made of graphite or the like.

[0022] The positive electrode plate 3 has positive electrode composite material layers 32 on both sides of a positive electrode current collector 31 serving as a positive electrode base material. The other end of the positive electrode current collector 31 is a positive electrode connection portion 33 where the metal is exposed. The positive electrode connection portion 33 is electrically connected to the positive electrode current collecting terminal 16. The positive electrode current collector 31 is composed of a conductive material made of a metal having good conductivity. The positive electrode current collector 31 is composed of, for example, an aluminum foil. As the positive electrode current collector 31, a material containing aluminum or a material containing an aluminum alloy can be used. The configuration of the positive electrode current collector 31 is not limited to this. The positive electrode current collector 31 serves as a base as an aggregate of the positive electrode composite material layer 32 and has a function of a current collecting member for collecting electricity from the positive electrode composite material layer 32.

[0023] The positive electrode composite layer 32 is formed by applying a positive electrode composite paste onto the positive electrode current collector 31 and drying it. The positive electrode composite layer 32 contains, in addition to the positive electrode active material, a conductive material, a binder, and additives such as a dispersant.

[0024] The particles of the positive electrode active material contain a layered crystal structure lithium transition metal oxide. The lithium transition metal oxide contains, in addition to lithium, one or more predetermined transition metal elements. The lithium transition metal oxide according to this embodiment includes, as an example, all of nickel, cobalt, and manganese.

[0025] As the binder, for example, polyvinylidene fluoride (PVdF), polytetrafluoroethylene (PTFE), polyacrylic acid, polyacrylate, etc. can be used. The negative electrode plate 2 and the positive electrode plate 3 are stacked via a separator 4 to form a laminate.

[0026] "Manufacturing process of lithium ion secondary battery" The manufacturing process of the lithium ion secondary battery includes a process of synthesizing the positive electrode active material. The synthesized positive electrode active material is partially sampled as a test sample at a predetermined sampling timing. Then, it is inspected whether the sampled sample meets the requirements.

[0027] "Inspection device for positive electrode active material" Fig. 3 shows the configuration of the inspection device for the positive electrode active material. The inspection device for the positive electrode active material includes an arithmetic unit 40. The arithmetic unit 40 includes a PU 42 and a storage device 44. The PU 42 is a software processing device such as a CPU and a GPU. The storage device 44 may be a non-volatile memory that cannot be electrically rewritten. The storage device 44 may also be a non-volatile memory that can be electrically rewritten and a storage medium such as a disk medium. The arithmetic unit 40 executes arithmetic processing for the inspection of the positive electrode active material by executing a program stored in the storage device 44. The arithmetic unit 40 acquires data via an input interface 50. The arithmetic unit 40 also outputs an arithmetic result via an output interface 52. The output interface 52 includes a display unit that displays image information.

[0028] "Part of the manufacturing process of a lithium-ion secondary battery" FIG. 4 shows a part of the manufacturing process of the lithium-ion secondary battery 1. In FIG. 4, the step numbers of each process are represented by numbers with "S" attached at the beginning.

[0029] In the series of processes shown in FIG. 4, first, the positive electrode active material is synthesized (S10). Next, a part of the synthesized positive electrode active material is sampled and measured by XRD (X-ray diffraction) (S12).

[0030] Next, the PU 42 acquires data regarding the measurement result of the step S12 input via the input interface 50 (S14). Then, the PU 42 executes a Rietveld analysis using the acquired data (S16). Here, the PU 42 uses the crystal structure base data 44a stored in the storage device 44.

[0031] FIG. 5 shows the crystal structure of the positive electrode active material defined by the crystal structure base data 44a. The model shown in Fig. 5 represents a crystal structure having a regular arrangement of oxygen 60, a transition metal composed of nickel 62, cobalt 64, and manganese, and lithium 66. Although manganese is not shown in Fig. 5 for the sake of layout, it actually exists in the vicinity of nickel 62 and cobalt 64.

[0032] Note that nickel and cobalt are not limited to the positions in Fig. 5. Any of the atoms of nickel, cobalt, or manganese may exist at the positions indicated by the symbols "62" and "64" in Fig. 5. Also, nickel, cobalt, and manganese are not limited to the case where they are regularly arranged, and they may be randomly arranged.

[0033] The crystal structure model shown in Fig. 5 represents a pure crystal structure in which cation mixing does not occur. Based on the spectral analysis of the data of the measurement results obtained based on the crystal structure shown in Fig. 5, PU42 calculates the ratio of cation mixing, which is the replacement of the transition metal and lithium 66. Cation mixing occurs in the above-described synthesis process.

[0034] Returning to FIG. 4, based on the results of the Rietveld analysis, PU42 creates a crystal structure model for the sample after grasping the ratio of cation mixing in the sample (S18). PU42 exchanges lithium 66 with nickel 62 etc. according to the ratio of cation mixing. As an example, PU42 exchanges the transition metal with lithium 66 under the condition that the variation in the distance between the positions where the transition metal is substituted with lithium 66 is minimized. Specifically, PU42 generates a crystal structure model in a state where the charge rate of the lithium-ion secondary battery 1 is equal to or higher than a predetermined value Sth. The charge rate is the ratio of the actual charge amount to the full charge amount of the lithium-ion secondary battery 1. The higher the charge rate, the greater the ratio of lithium 66 being removed in the crystal structure shown in FIG. 5. PU42 creates a model in which a part of lithium 66 is removed from the base crystal structure shown in FIG. 5 according to the charge rate. Note that the predetermined value Sth may be, for example, a value of "0.8 (80 percent)" or more.

[0035] The model created by the process of S18 is a model in which a part of lithium 66 is missing and a part of lithium 66 and a part of the transition metal are exchanged in the crystal structure shown in FIG. 5.

[0036] Next, PU42 sets a temperature T for performing molecular dynamics calculations using the above-created crystal structure model (S20). The initial value of the temperature T is, for example, a predetermined value equal to or higher than room temperature. The initial value may be, for example, about 500 Kelvin.

[0037] PU42 performs molecular dynamics calculations on the above-created crystal structure model at the temperature T using a machine learning force field (S22). Here, the machine learning force field is, for example, a graphical neural network (GNN) force field. The GNN is, for example, M3GNet. The model data 44b, which is the data defining this trained model, is stored in the storage device 44 shown in FIG. 1.

[0038] PU42 inputs the temperature T and the crystal structure model created by the process of S18 into the model defined by the model data 44b. Specifically, the input of the crystal structure model is the input of graph data. That is, the nodes, edges, atomic coordinates, crystal lattice matrix, etc. determined by the crystal structure created by the process of S18 are input. Here, the nodes represent atoms. That is, a value specifying the type of atom is assigned to the nodes. Also, the edges are variables indicating the bonds between atoms. The crystal lattice matrix is a matrix determined by the crystal structure created by the process of S18.

[0039] The output of the learned model includes the atomic coordinates at the elapsed time t of the specified time. The specified time t is set to a time shorter than 1 second as an example. PU42 calculates the mean squared displacement (MSD) between the coordinates ri(t + t0) of the transition metal output by the learned model and the coordinates ri(t0) of the transition metal input to the learned model (S24). Here, the variable i is a variable for identifying the transition metal. Also, the value N shown in FIG. 4 is the number of transition metals among the node variables input to the learned model. That is, PU42 calculates the mean squared displacement of all transition metals.

[0040] Next, PU42 determines whether or not the mean squared displacement is zero (S26). This process is a process for determining whether or not cation mixing has occurred. That is, when cation mixing has occurred, since the transition metal is replaced with lithium 66, the coordinate ri(t + t0) at the elapsed time t of the specified time deviates from the coordinate ri(t0) as illustrated in FIG. 6. In the present embodiment, whether or not cation mixing has occurred is quantified by the mean squared displacement.

[0041] When PU42 determines that the mean squared displacement is zero (S26: YES), after raising the temperature T by a predetermined amount Δ (S28), it proceeds to the process of S22. On the other hand, when PU42 determines that the mean squared displacement is greater than zero (S26: NO), it determines whether the temperature T(n - 1) when it was last determined that the mean squared displacement was zero is equal to or higher than the threshold value Tth (S30). Here, the temperature T(n - 1) is the upper limit temperature at which cation mixing does not occur. The process of S30 is a process of determining whether the upper limit temperature at which cation mixing does not occur is equal to or higher than the threshold value Tth.

[0042] When PU42 determines that the temperature T(n - 1) is equal to or higher than the threshold value Tth (S30: YES), it determines that it is qualified (S32). In other words, PU42 determines that there is no problem in the synthesis process of the positive electrode active material. On the other hand, when PU42 determines that the temperature T(n - 1) is less than the threshold value Tth (S30: NO), it feeds back to the process of synthesizing the positive electrode active material that there is such a situation (S34). As a result, by changing various adjustment factors in the synthesis process, the synthesis process of the positive electrode active material is corrected.

[0043] Note that when PU42 completes the processes of S32 and S34, it temporarily ends the series of processes shown in FIG. 4. Incidentally, the processes of S14 to S34 are realized by PU42 executing the program stored in the storage device 44.

[0044] "Operations and Effects of the Present Embodiment" PU42 executes molecular dynamics calculations using the crystal structure of the sample of the positive electrode active material while increasing the temperature T by a predetermined amount Δ each time. Then, PU42 regards the upper limit temperature at which no mean squared displacement occurs as the upper limit temperature at which no cation mixing occurs. When the upper limit temperature at which no cation mixing occurs is equal to or higher than the threshold value Tth, PU42 determines that the positive electrode active material meets the requirements.

[0045] FIG. 7 shows the mean squared displacement when the temperature T is increased. In the example shown in FIG. 7, among the temperatures T1 to T5, only the temperature T1 has a mean squared displacement of zero after the specified time t. Therefore, the temperature T1 is the upper limit temperature.

[0046] This makes it possible to determine whether or not, during a predetermined usage period, deterioration due to accelerated cation mixing in the lithium-ion secondary battery 1 occurs. Here, the predetermined usage period may be, for example, a period during which a vehicle equipped with the lithium-ion secondary battery 1 reaches a predetermined driving distance. The predetermined driving distance may be, for example, 100,000 km or more. The predetermined usage period may be a period until a predetermined time has elapsed since the lithium-ion secondary battery 1 was mounted on the vehicle. The predetermined time may be, for example, a period of 10 years or more.

[0047] The above specified time t is an extremely short time. By predicting the atomic displacement at the elapse of the extremely short time, it is possible to grasp the state after the above predetermined usage period because the temperature T used in the molecular dynamics calculation is extremely high compared to the temperature range in which the actual lithium-ion secondary battery 1 is used. That is, when the temperature of the lithium-ion secondary battery 1 is excessively high, the deterioration of the lithium-ion secondary battery 1 is accelerated. Therefore, the higher the temperature T of the lithium-ion secondary battery 1 during the molecular dynamics calculation, the more the result of the molecular dynamics calculation can be regarded as the result after longer-term use of the lithium-ion secondary battery 1.

[0048] The above threshold value Tth is set according to the predetermined usage period. According to the present embodiment described above, the following operations and effects can be obtained. (1) The accuracy in predicting the diffusion of transition metals due to the use of the lithium-ion secondary battery 1 depends on the accuracy of the crystal structure information. Here, during the production of the positive electrode active material, cation mixing can occur to some extent. Therefore, PU42 predicts the diffusion of transition metals using crystal structure information including the ratio of cation mixing in the sample. Thereby, the prediction accuracy can be improved.

[0049] (2)PU42 calculated the diffusion of transition metals when the state of charge of the lithium-ion secondary battery 1 was equal to or greater than a predetermined value Sth. When the state of charge is large, the rate of deterioration of the positive electrode active material is greater than when the state of charge is small. Therefore, by predicting the diffusion of transition metals when the state of charge is equal to or greater than the predetermined value Sth using PU42, the specified time t can be made shorter compared to the case where the state of charge is less than the predetermined value Sth.

[0050] (3)PU42 calculates the ratio of cation mixing by Rietveld analysis of the positive electrode active material. As a result, the ratio of cation mixing can be calculated using simpler equipment than when performing STEM observation or the like.

[0051] (4)PU42 calculated the time change of the coordinates of transition metals by inputting a crystal structure model of the positive electrode active material into a learned model. As a result, it is possible to achieve a suitable compromise between calculating the time change of the coordinates of transition metals with high accuracy and calculating without increasing the computational load.

[0052] (5)In the manufacturing process of the lithium-ion secondary battery 1, the positive electrode active material synthesized at predetermined intervals was made the subject of the process shown in FIG. 4. As a result, the process of synthesizing the positive electrode active material can be evaluated. Therefore, when there is a change in the quality of the positive electrode active material generated by the synthesis process during mass production of the lithium-ion secondary battery 1, the synthesis process can be corrected.

[0053] Here, the process shown in FIG. 4 is an inspection that substitutes for a charge-discharge test in which the mass-produced lithium-ion secondary battery 1 is sampled, or a test in which the positive electrode active material is stored under predetermined conditions and the presence or absence of its deterioration is inspected. Further, the process of S22 is a process of executing a simulation. Therefore, an inspection that substitutes for a charge-discharge test in which the mass-produced lithium-ion secondary battery 1 is sampled, or a test in which the positive electrode active material is stored under predetermined conditions and the presence or absence of its deterioration is inspected can be executed in a short time.

[0054] <Corresponding relationship> The correspondence between the matters in the above embodiment and the matters described in the column of "Means for Solving the Problems" is as follows. Below, the correspondence is shown for each number of the solution means described in the column of "Means for Solving the Problems". [1,4] The non-aqueous electrolyte secondary battery corresponds to the lithium-ion secondary battery 1. The acquisition step corresponds to the steps of S14 and S16. The prediction step corresponds to the steps of S20 to S22. The evaluation step corresponds to the steps of S24 to 30. [2] The upper limit value of the temperature at which the transition metal does not diffuse corresponds to the temperature T(n - 1). [3] The prediction step corresponds to the execution in which the crystal structure model with the charging rate set to a predetermined value Sth or more in the step of S18 is used as the input of the learned model. The computer corresponds to PU42. [5] The learned model corresponds to the model defined by the model data 44b. [6] The synthesis step corresponds to the step of S10. The feedback step corresponds to the step of S34.

[0055] <Other Embodiments> Note that this embodiment can be implemented with the following modifications. This embodiment and the following modification examples can be implemented in combination with each other within a technically non-conflicting range.

[0056] "Regarding the Acquisition Step" · The Rietveld analysis is not limited to the process using the measurement data by XRD. For example, the Rietveld analysis may be a process using the measurement data by the neutron diffraction method.

[0057] · It is not essential that the process of acquiring the crystal structure information includes the Rietveld analysis. For example, the process of acquiring the crystal structure information by an electron microscope may be used. Specifically, for example, the ratio of cation mixing in the crystal may be counted by STEM observation.

[0058] "Regarding the Crystal Structure Model" ·In the crystal structure model, the transition metal to be substituted with lithium according to the ratio of cation mixing is not limited to the one that minimizes the variation in the distance between the substituted transition metals. For example, in the crystal structure model, the transition metal to be substituted with lithium according to the ratio of cation mixing may be a randomly selected transition metal.

[0059] Furthermore, for example, as described in the column of "Regarding the acquisition process" above, when performing STEM observation, the transition metal to be substituted with lithium may be determined faithfully according to the actual observation results.

[0060] ·As described in the column of "Regarding the positive electrode active material" below, when the transition metal element does not include all of nickel, cobalt, and manganese, the crystal structure-based data 44a may be changed accordingly.

[0061] "Regarding the prediction process" ·The prediction process is not limited to the process executed assuming that the charging rate is a constant value. For example, the prediction process may be a process of predicting the diffusion of atoms separately for each case where various values are set for the charging rate. In that case, PU42 may be determined to be qualified, for example, when the temperature T(n - 1) at all charging rates is equal to or higher than the threshold value Tth.

[0062] ·It is not essential that the prediction process is a process of predicting the diffusion at a temperature excessively higher than the temperature assumed during the use of the lithium-ion secondary battery 1. For example, the diffusion of atoms at the time when the required usable time of the lithium-ion secondary battery 1 has elapsed may be predicted. In that case, the temperature may be the temperature assumed during the use of the lithium-ion secondary battery 1.

[0063] · The pre-trained model used for molecular dynamics calculations is not limited to M3GNet. The pre-trained model used for molecular dynamics calculations may be, for example, Open Catalyst. Furthermore, it is not essential that the architecture of the pre-trained model used for molecular dynamics calculations is a graphical neural network.

[0064] · The molecular dynamics calculation method used to predict the diffusion of transition metals is not limited to the method using a pre-trained model. The molecular dynamics calculation method may be, for example, a method using density functional theory (DFT). Also, the molecular dynamics calculation method may be, for example, a method using a classical force field.

[0065] "Regarding the evaluation process" · It is not essential that the evaluation result of the evaluation process is only the comparison result of the magnitude between the temperature T(n - 1) and the threshold value Tth. For example, when it is determined that the temperature T(n - 1) is equal to or higher than the threshold value Tth, the magnitude of the temperature T(n - 1) may be included in the evaluation result.

[0066] · The evaluation process is not limited to the process of comparing the upper limit value of the temperature that has not diffused at the time when an extremely short time has elapsed with the threshold value. The evaluation process may be, for example, a process of evaluating as normal when it is determined that there is no diffusion of the transition metal. This is effective when predicting the diffusion of atoms at the time when the required usable time of the lithium-ion secondary battery 1 has elapsed, as described in the section "Regarding the prediction process".

[0067] "Regarding the use of the evaluation process" · It is not essential that the evaluation result of the evaluation process is used as feedback information for reviewing the synthesis process of the positive electrode active material. For example, the evaluation result may be used to determine various conforming elements of the synthesis process of the positive electrode active material.

[0068] ·The evaluation result of the evaluation process does not have to be utilized during the manufacturing of the lithium-ion secondary battery 1 as a battery cell. For example, when multiple battery cells are modularized and shipped, the evaluation result may be used to select the battery cells to be the same module. For example, as described in the above "Regarding the evaluation process", when the magnitude of the upper limit temperature T(n - 1) is included in the comparison result, the evaluation result used here may be the upper limit temperature T(n - 1). Thereby, for example, those with similar upper limit temperatures T(n - 1) can be made into the same module.

[0069] ·The evaluation result of the evaluation process does not have to be utilized during the manufacturing of the lithium-ion secondary battery 1. For example, the evaluation result may be used for the evaluation of the reusability of a used and recovered lithium-ion secondary battery 1. For example, as described in the above "Regarding the evaluation process", when the magnitude of the upper limit temperature T(n - 1) is included in the comparison result, the evaluation result used here may be the upper limit temperature T(n - 1). Thereby, for example, it can be determined that the higher the upper limit temperature T(n - 1), the higher the possibility that the battery can be reused. When using the evaluation result in this way, after storing the data indicating the evaluation result in a two-dimensional code or the like, a sticker with the code attached may be pasted on the lithium-ion secondary battery 1.

[0070] "Regarding the computer" ·The computer is not limited to those that execute software processing. For example, it may be provided with a dedicated hardware circuit such as an ASIC that executes at least a part of the processing executed in the above-described embodiment. That is, the computer only needs to include a processing circuit having any one of the following configurations (a) to (c). (a) A processing circuit including a processing device that executes all of the above processing according to a program, and a program storage device such as a storage device that stores the program. (b) A processing circuit including a processing device and a program storage device that execute a part of the above processing according to a program, and a dedicated hardware circuit that executes the remaining processing. (c) A processing circuit including a dedicated hardware circuit that executes all of the above processing. Here, there may be a plurality of software execution devices including a processing device and a program storage device. Also, there may be a plurality of dedicated hardware circuits.

[0071] "Regarding the positive electrode active material" ·The transition metal element contained in the lithium transition metal oxide contained in the positive electrode active material is preferably at least one of nickel, cobalt, and manganese.

[0072] ·In addition to the transition metal element (that is, at least one of nickel, cobalt, and manganese), the positive electrode active material may additionally contain one or more kinds of elements. The additional element of the positive electrode active material may be an element belonging to Group 1 of the periodic table (alkali metals such as sodium). The additional element of the positive electrode active material may be a metal belonging to Group 2 (alkaline earth metals such as magnesium and calcium). The additional element of the positive electrode active material may be a metal belonging to Group 4 (transition metals such as titanium and zirconium). The additional element of the positive electrode active material may be a metal belonging to Group 6 (transition metals such as chromium and tungsten). The additional element of the positive electrode active material may be a metal belonging to Group 8 (transition metals such as iron). The additional element of the positive electrode active material may be an element belonging to Group 13 (boron, a semi-metal element, or a metal such as aluminum) and Group 17 (halogens such as fluorine).

Explanation of symbols

[0073] 1…Lithium-ion secondary battery 2…Negative electrode plate 3…Positive electrode plate 11…Battery case 12…Electrode body 13…Non-aqueous electrolyte 14…Positive electrode external terminal 15…Negative electrode external terminal 21…Negative electrode current collector 22…Negative electrode composite layer 23…Negative electrode connection part 31…Positive electrode current collector 32…Positive electrode composite layer 40…Arithmetic unit 44…Memory device 44a…Crystal structure-based data 44b…Model data 60…Oxygen 62…Nickel 64…Cobalt 66…Lithium

Claims

1. A method for inspecting a positive electrode active material constituting a non-aqueous electrolyte secondary battery, comprising: an acquisition step, a prediction step, and an evaluation step; the acquisition step is a step of acquiring crystal structure information of the synthesized positive electrode active material; the crystal structure information includes the ratio of cation mixing; the prediction step is a step of predicting the diffusion of a transition metal constituting the positive electrode active material by computer-aided molecular dynamics calculation according to the crystal structure information; the evaluation step is a method for inspecting a positive electrode active material, which is a step of evaluating the quality of the positive electrode active material according to the result of the prediction step.

2. the prediction step is a step of predicting the diffusion of the transition metal by computer for each case where the temperature of the positive electrode active material is set variously; the evaluation step includes a step of evaluating that the quality of the positive electrode active material meets the requirements when the upper limit value of the temperature at which the transition metal does not diffuse among the results of the prediction step is equal to or higher than a threshold value. The method for inspecting a positive electrode active material according to Claim 1.

3. The method for inspecting a positive electrode active material according to Claim 2, wherein the prediction step is a step of predicting the diffusion of the transition metal by computer in a state where the charge rate of the non-aqueous electrolyte secondary battery is equal to or higher than a predetermined value.

4. The method for inspecting a positive electrode active material according to Claim 1, wherein the acquisition step includes a process of calculating the ratio of cation mixing by Rietveld analysis of the positive electrode active material.

5. The method for inspecting a positive electrode active material according to Claim 1, wherein the prediction step includes a step of predicting the time change of the coordinates of the transition metal by computer by inputting a crystal structure model of the positive electrode active material into a learned model.

6. A method for manufacturing a non-aqueous electrolyte secondary battery, comprising: a synthesis step of synthesizing a positive electrode active material constituting the non-aqueous electrolyte secondary battery; the acquisition step, the prediction step, and the evaluation step in the method for inspecting a positive electrode active material according to Claim 1; a feedback step of feeding back the result of the evaluation step to the synthesis step when the quality of the positive electrode active material is not evaluated as meeting the requirements by the evaluation step. A method for manufacturing a non-aqueous electrolyte secondary battery.

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