Method for Determining Residual Alkali in Cathode Material for Composite Phase Sodium-Ion Batteries

Abstract

This application relates to the field of material testing technology, and specifically relates to a method for determining residual alkali in the cathode material of a composite-phase sodium ion battery. The method includes: obtaining the spectrum of the powder to be measured and recording it as the target spectrum; segmenting the curve in the target spectrum, and calculating the intensity characteristic coefficient of the curve segment according to the difference in the intensity of each peak sequence and the number of peak sequences; screening the curve segments according to the magnitude of the intensity characteristic coefficient to obtain the characteristic segments; obtaining the difference in the peak change according to the difference in the slopes of the increasing and decreasing sequences on both sides of the peak point and the peak angle in the characteristic segments, and obtaining the similarity degree of the two spectra according to the set of peak angles, the difference in peak change, and the difference in peak sequences; collecting multiple standard solutions, fitting the curve equation through the similarity degree of the spectra of multiple standard solutions, and substituting the similarity degree of the spectrum of the powder to be measured and the spectrum of the standard solution into the content of the chemical substance of the powder to be measured. This application improves the accuracy of residual alkali determination.

Description

Technical Field

[0001] This application relates to the technical field of electrical variable measurement, and specifically to a method for determining residual alkali in the cathode material of a composite-phase sodium-ion battery. Background Art

[0002] Sodium-ion batteries (SIBs) are considered to be one of the important candidates to replace lithium-ion batteries due to their rich resources, low cost, and similar working principles to lithium-ion batteries. However, the performance of sodium-ion batteries depends to a large extent on the design and synthesis of their cathode materials. During the synthesis of cathode materials, some sodium salts will form alkaline substances on the material surface after sintering. These alkaline substances are prone to absorbing water and getting damp, which will affect the processing performance. At the same time, decomposition under high voltage will also cause the battery to swell. Therefore, how to effectively detect the residual alkali content in the cathode material has become one of the key issues. Currently, the main method for determining the residual alkali in the cathode material of sodium-ion batteries is potentiometric titration. The working principle is an acid-base neutralization reaction, which involves the judgment of the pH values at two potential mutation points. However, in the prior art, the threshold range of the pH values at the mutation points is often given. Therefore, when measuring multiple times, the measurement results are unstable, affecting the stability of the production of cathode materials.

[0003] The XRD pattern is relatively stable and accurate when measuring chemical substances in a solution. At the same time, when the content of chemical substances in the solution changes, the XRD pattern will also change. Therefore, it has become one of the solutions to ensure the stability and accuracy of residual alkali determination. According to the XRD pattern difference between the test solution and the standard solution, the residual alkali can be determined, and at the same time, the problem of unstable measurement results multiple times can be avoided. However, when using existing methods such as the spectral angle algorithm to perform similarity comparison of complex data, the similarity measurement is often carried out through the entire XRD pattern. However, the chemical substances in the solution only affect the intensity of specific diffraction angles, and only these changes are meaningful for the determination of residual alkali. If considered as a whole, the remaining fluctuations will affect the accuracy of similarity judgment, and further affect the accuracy of residual alkali determination. Therefore, a more accurate similarity comparison method is needed to ensure the accurate and stable determination of residual alkali. Summary of the Invention

[0004] In order to solve the technical problem that useless curve fluctuations affect the measurement accuracy, this application provides a method for determining residual alkali in the cathode material of a composite-phase sodium-ion battery. The specific technical solution adopted is as follows:

[0005] This application proposes a method for determining residual alkali in the cathode material of a composite-phase sodium-ion battery. The method includes the following steps:

[0006] Obtain the pattern of the measured powder and record it as the target pattern;

[0007] Segment the curves in the target spectrum and obtain the peak sequences for each segment; obtain the prominence of the peak sequences based on the intensity differences between the elements in the peak sequences; obtain the intensity characteristic coefficients for the curve segments corresponding to the peak sequences based on the coefficient of variation of the peak sequences, the differences in prominence between this peak sequence and the other peak sequences, and the number of peak sequences; screen the curve segments according to the magnitudes of the intensity characteristic coefficients to obtain the characteristic segments;

[0008] Obtain the peak points in the characteristic segments, and obtain the increasing sequence and decreasing sequence of the peak points based on the intensity values of the adjacent points of the peak points; perform fitting on the increasing sequence and decreasing sequence respectively to obtain the fitting straight lines and fitting curves for the corresponding sequences; determine the peak angle set based on the peaks of the characteristic segments of the spectrum; obtain the peak corresponding wave crest change differences based on the differences in the slopes of the increasing sequences, the differences in the slopes of the decreasing sequences, and the differences in the fitting curves of the peaks corresponding to the same diffraction angle in different spectra; determine whether the similarity degree is 0 based on the intersection of the peak angle sets of the two spectra, and obtain the similarity degree between the two spectra based on the differences in the wave crest sequences of all the characteristic segments of the two spectra, the intersection-union ratio of the peak angle sets, and the wave crest change differences of all the peaks in the intersection of the peak angle sets;

[0009] Collect the standard solutions multiple times, obtain the spectra of the standard solutions and the contents of different chemical substances, and construct a fitting curve equation based on the similarity degree between the spectra of the standard solutions and the contents of the chemical substances; substitute the similarity degree between the spectrum of the measured powder and the spectrum of the standard solution into the fitting curve equation to form a system of equations to calculate the contents of multiple chemical substances in the measured powder, and complete the determination of the residual alkali.

[0010] In the above solution, the present application calculates the intensity characteristic coefficient according to the change trend of the intensities of each diffraction angle in the XRD pattern of the residual alkali powder. This coefficient enhances the accuracy of feature extraction in the XRD pattern, extracts the feature segments of the XRD pattern, and further enhances the accuracy of subsequent similarity measurement. Then, according to the change situation on both sides of the peak and the peak characteristics in the feature segments of the two XRD patterns, the similarity degree of the patterns is calculated. This similarity degree improves the accuracy of the similarity measurement of the XRD pattern, and further improves the accuracy of the determination of the residual alkali. Finally, curve fitting is performed through the chemical substance content in the standard solution, thereby enhancing the stability of multiple residual alkali determinations. In this way, according to the characteristic that the change of chemical substances in the residual alkali solution will cause the change of the XRD pattern, the similarity between two different XRD patterns is measured by using the characteristic change of the XRD pattern, enhancing the accuracy of the similarity measurement. Subsequently, by measuring the similarity of the XRD patterns between the residual alkali solution and the standard solution, the content of each chemical substance in the solution to be measured is determined, thus completing the determination of the residual alkali. This method enhances the accuracy of the similarity measurement of the XRD pattern, and further improves the accuracy of the determination of the residual alkali. By comparing with the standard solution, the content of each chemical substance can be obtained, and the stability during multiple measurements is ensured, thereby ensuring the stability of the production of the cathode material of the battery.

[0011] In one embodiment, the method for segmenting the curve in the target pattern and obtaining the peak sequence of each segment is as follows:

[0012] The curve in the target pattern is evenly divided into several curve segments, the peak data in each segment is extracted, and according to the size order of the diffraction angles corresponding to the peaks, the peak sequences of each segment are respectively formed, that is, each curve segment corresponds to a peak sequence.

[0013] In one embodiment, the method for obtaining the prominence degree of the peak sequence according to the intensity difference between elements in the peak sequence is as follows:

[0014] The prominence degree of the peak sequence is positively correlated with the intensity difference between elements.

[0015] In one embodiment, the method for obtaining the intensity characteristic coefficient of the curve segment corresponding to the peak sequence according to the coefficient of variation of the peak sequence, the difference in the prominence degree between this peak sequence and the other peak sequences, and the number of peak sequences is as follows:

[0016] The intensity characteristic coefficient of the curve segment corresponding to the peak sequence is positively correlated with the coefficient of variation of the peak sequence and the difference in the prominence degree between this peak sequence and the other peak sequences, and is negatively correlated with the number of peak sequences.

[0017] In one embodiment, the method for obtaining the peak points in the feature segmentation and obtaining the increasing sequence and decreasing sequence of the peak points according to the intensity values of the adjacent points of the peak points is as follows:

[0018] Perform polynomial fitting on all data points of the feature segmentation to obtain the fitting curve of the feature segmentation. Take the derivative of the function of the fitting curve to obtain the extreme points, and screen the peak points among the extreme points according to the positive and negative properties on the left and right sides of the extreme points; form an increasing sequence with the intensity values corresponding to all adjacent points with positive derivatives on the left side of the peak point, and form a decreasing sequence with the intensity values corresponding to all adjacent points with negative derivatives on the right side of the peak point.

[0019] In one embodiment, the method for determining the peak angle set according to the peaks of the feature segmentation of the spectrum is as follows:

[0020] Obtain the peaks of each feature segmentation of the spectrum, and denote the set composed of the diffraction angles corresponding to all the peaks as the peak angle set.

[0021] In one embodiment, the method for obtaining the peak change difference corresponding to the peak according to the difference in the slopes of the increasing sequences, the difference in the slopes of the decreasing sequences, and the difference in the fitting curves of the peaks corresponding to the same diffraction angle of different spectra is as follows:

[0022] , where is the slope ratio of the fitting lines of the t-th monotonic sequence of the wave peaks at the -th diffraction angle of the two spectra, is the absolute value of the difference in the integral areas of the fitting curves of the t-th monotonic sequence of the wave peaks at the -th diffraction angle of the two spectra, takes values of 1 and 2 corresponding to the increasing sequence and decreasing sequence of the wave peak respectively, represents the peak change difference of the peak corresponding to the

[0023] In one embodiment, the method for determining whether the similarity degree is 0 according to the intersection of the peak angle sets of the two spectra, and obtaining the similarity degree between the two spectra according to the difference in the wave peak sequences of all feature segments of the two spectra, the intersection-union ratio of the peak angle sets, and the peak change differences of all peaks in the intersection of the peak angle sets is as follows:

[0024] If the intersection of the peak angle sets corresponding to the two spectra is an empty set, then set the similarity degree of the two spectra to 0;

[0025] If the intersection of the peak angle sets corresponding to the two spectra is not an empty set, the expression for the similarity degree between the two spectra is:

[0026] , The cosine angle between the sequence composed of the peak sequences of all characteristic segments of the spectrum of powder u and the sequence composed of the peak sequences of all characteristic segments of the spectrum of powder v Represents the intersection of the peak angle sets of powder u and powder v Represents the Difference in peak variation corresponding to the peak at the diffraction angle Represents the intersection-union ratio of the peak angle sets of powder u and powder v Is a parameter adjustment coefficient to avoid a denominator of 0 Represents the similarity degree of the spectra corresponding to powder u and powder v

[0027] In one embodiment, the method for collecting multiple standard solutions, obtaining the spectra of the standard solutions and the contents of different chemical substances, and constructing a fitting curve equation based on the similarity degree of the spectra between the standard solutions and the contents of the chemical substances is as follows:

[0028] Obtain the spectra of multiple standard solutions, combine the standard solutions in pairs, calculate the similarity degree between the spectra of any two standard solutions, use all the similarity degrees as the dependent variable, and the difference in the contents of various chemical substances in the corresponding standard solutions as the independent variable. Adopt multiple nonlinear regression for non-linear output fitting curve equation, and record the fitting curve equation as the residual alkali difference curve

[0029] In one embodiment, the method for substituting the similarity degree between the spectrum of the measured powder and the spectrum of the standard solution into the fitting curve equation to form a system of equations for calculating the contents of multiple chemical substances in the measured powder is as follows:

[0030]

[0031] Where Are respectively the contents of the 1st to qth chemical substances in the measured powder 、 、…、 Are respectively the similarity degrees between the spectra of standard solution 1, standard solution 2, standard solution And the spectrum of the measured powder Is the residual alkali difference curve function Is the Content of the hth chemical substance in the th standard solution , , 。 BRIEF DESCRIPTION OF THE DRAWINGS

[0032] To more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0033] Figure 1 Flowchart of the method for measuring residual alkali applied to the cathode material of a composite-phase sodium-ion battery provided by an embodiment of the present application. Detailed implementation manners

[0034] In order to further elaborate on the technical means and effects adopted by the present application to achieve the intended invention purpose, the following will, in conjunction with the accompanying drawings and preferred embodiments, describe in detail the specific implementation manners, structures, features, and effects of the method for measuring residual alkali applied to the cathode material of a composite-phase sodium-ion battery proposed according to the present application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0035] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present application belongs.

[0036] Embodiment of the method for measuring residual alkali applied to the cathode material of a composite-phase sodium-ion battery:

[0037] The following will specifically describe the specific solution of the method for measuring residual alkali applied to the cathode material of a composite-phase sodium-ion battery provided by the present application with reference to the accompanying drawings.

[0038] Please refer to Figure 1 , which shows the flowchart of the method for measuring residual alkali applied to the cathode material of a composite-phase sodium-ion battery provided by an embodiment of the present application. The method includes the following steps:

[0039] Step S001, obtain the spectrum of the measured powder and record it as the target spectrum.

[0040] Use absolute ethanol as a solvent to dissolve the residual alkali on the surface of the cathode material of the composite-phase sodium-ion battery. After filtration, take the filtrate as the measurement solution, and this measurement solution is the residual alkali solution of the cathode material. Then place the measurement solution in an oil bath and stir until the solvent evaporates completely. The temperature of the oil bath is 60 , and this powder is called the measured powder. Then use an XRD ray scanner to perform X-ray diffraction analysis (XRD) on the measured powder to obtain the XRD spectrum, which is recorded as the target spectrum. In this embodiment, the radiation source is Cu, Ka, and the scanning range is 10~80 , the scanning speed is .

[0041] So far, the target spectrum has been obtained.

[0042] Step S002: Segment the curves in the target spectrum, calculate the intensity characteristic coefficients of the curve segments according to the differences in the intensity of each peak sequence and the number of peak sequences; screen the curve segments according to the magnitudes of the intensity characteristic coefficients to obtain the characteristic segments.

[0043] When the traditional potentiometric titration method is used to detect the residual alkali, the pH value at the mutation point cannot be accurately determined. Therefore, the measurement effect of the residual alkali is closely related to the error degree of the pH value. When performing multiple measurements of the residual alkali, due to the instability of the pH value at the mutation point, the results of different batches of residual alkali measurements are also unstable.

[0044] When manufacturing the cathode material using the same process, for the two powders, although the amount of residual alkali may not be exactly the same, the chemical substances in them are relatively close, and the positions and peak intensities of each chemical substance in the target spectrum are relatively consistent. Thus, the closer the target spectra of the two powders are, the closer the chemical substances in the two powders are, that is, the closer the residual alkalis of the two powders are.

[0045] Therefore, the spectral angle algorithm can be used to compare two target spectra; however, the traditional spectral angle algorithm measures the similarity of complex data by measuring the overall similarity of the curves. However, in the target spectrum, the curves are constantly fluctuating, but only those diffraction angle and intensity combinations corresponding to chemical substances with obvious fluctuations are significantly meaningful for the detection of powder similarity, while the contribution of the remaining majority of fluctuations is small. If the overall curve is still used to measure the similarity, it will cause a large error in the results. Therefore, it is necessary to extract the features with significant meaning in the target spectrum and use these features for similarity judgment to make the results more accurate.

[0046] When performing XRD analysis on the powder, each chemical substance in the powder corresponds to a unique combination, which reflects different intensities corresponding to different diffraction angles. The abscissa of the target spectrum is the diffraction angle, and the ordinate is the intensity corresponding to different diffraction angles. And the intensity pays more attention to the peaks in the target spectrum. Therefore, when extracting features in the target spectrum, greater weight needs to be given to the peak data. However, since the curves are constantly fluctuating throughout the target spectrum, not all peaks are significantly meaningful. Therefore, it is necessary to further screen the peaks according to the change characteristics of the peaks.

[0047] When performing XRD analysis on the powder, each chemical substance in the powder will show a sudden increase in intensity at some specific diffraction angles, while the fluctuations at other positions on the curve tend to be small because there is no corresponding chemical substance at the corresponding diffraction angles. Secondly, throughout the curve of the target spectrum, except for the increase in intensity of chemical substances at some specific diffraction angles, there is no corresponding chemical substance at most of the remaining diffraction angles, so the corresponding intensities are relatively close.

[0048] Divide the curve in the target spectrum evenly into segments. In this embodiment, is taken as 20. Extract the peak data in each segment and form a peak sequence for each segment in the order of the diffraction angles corresponding to the peaks, that is, each curve segment corresponds to a peak sequence.

[0049] First, for each peak sequence, obtain the prominence of the peak sequence according to the intensity difference between the elements in the peak sequence.

[0050] The prominence of the peak sequence is positively correlated with the intensity difference between the elements.

[0051] It should be noted that positive correlation means that when one variable increases, the other variable also increases, and the change directions of the two variables are the same. When one variable changes from large to small or from small to large, the other variable also changes from large to small or from small to large; the specific relationship is determined by the actual application, and this application does not make special restrictions.

[0052] Preferably, in this embodiment, calculate the absolute value of the difference in the intensities of all elements in the peak sequence, and calculate the average value of all the absolute values of the differences as the prominence of the peak sequence.

[0053] Preferably, in another embodiment of the present application, calculate the standard deviation of the intensities of all elements in the peak sequence, and take the standard deviation as the prominence of the peak sequence.

[0054] Obtain the intensity characteristic coefficient of the curve segment corresponding to the peak sequence according to the coefficient of variation of the peak sequence, the difference in prominence between this peak sequence and the other peak sequences, and the number of peak sequences.

[0055] The intensity characteristic coefficient of the curve segment corresponding to the peak sequence is positively correlated with the coefficient of variation of the peak sequence and the difference in prominence between this peak sequence and the other peak sequences, and is negatively correlated with the number of peak sequences.

[0056] It should be noted that negative correlation means that when one variable increases, the other variable decreases accordingly, and the changing directions of the two variables are opposite. When one variable changes from large to small or from small to large, the other variable also changes from small to large or from large to small. The specific relationship is determined by actual applications, and no special restrictions are imposed in this application.

[0057] Preferably, in this embodiment, the expression of the intensity characteristic coefficient is:

[0058] ; is the intensity characteristic coefficient of the curve segment corresponding to the th peak sequence, is the th peak sequence 's coefficient of variation, is the number of peak sequences, is the prominence degree in the th peak sequence, is the prominence degree in the th peak sequence, represents the th peak sequence.

[0059] Preferably, in another embodiment of this application, the expression of the intensity characteristic coefficient is:

[0060] , is the intensity characteristic coefficient of the curve segment corresponding to the th peak sequence, is the th peak sequence 's coefficient of variation, is the number of peak sequences, is the prominence degree in the th peak sequence, is the prominence degree in the th peak sequence, represents the th peak sequence.

[0061] It can be understood that when there is a peak of the diffraction angle corresponding to the chemical substance in the th segment, this peak will increase significantly, resulting in a relatively large difference within the curve segment, that is, the coefficient of variation is relatively large. Secondly, on the curve, only the intensity at specific diffraction angles is relatively large, and the intensity at the remaining diffraction angles is relatively small, that is, the prominence degree of the peak sequences of most segments is relatively small. Therefore, when there is a significant increase in the peak in the th segment, the difference between the prominence degree of the peak sequence of this segment and the prominence degree of the peak sequences of the other segments is relatively large. So when the When there is a peak corresponding to the diffraction angle of the chemical substance in the segment, the intensity characteristic coefficient is larger, and the more violent the fluctuation of the peaks in the segment is, the larger it is, indicating that the data change in this segment can better reflect the chemical substances in the powder. On the contrary, when there is no peak corresponding to the diffraction angle of the chemical substance in the segment, it is smaller, indicating that this segment contributes less to measuring the chemical substances in the powder.

[0062] By the above method, calculate the intensity characteristic coefficients of all curve segments, and then classify all curve segments into two categories according to the intensity characteristic coefficients. Take the curve segments of the category with a larger average intensity characteristic coefficient as the characteristic segments of the target spectrum. In this embodiment, take the intensity characteristic coefficients of all segments as the input, adopt the Otsu threshold segmentation algorithm, input the segmentation threshold, and mark the segments with intensity characteristic coefficients greater than the segmentation threshold as the characteristic segments of the target spectrum. The Otsu threshold segmentation algorithm is a well-known technology and will not be elaborated here.

[0063] So far, all the characteristic segments of the target spectrum have been obtained.

[0064] Step S003, obtain the peak change difference according to the difference in the slopes of the increasing and decreasing sequences on both sides of the peak point and the peak angle in the characteristic segment, and obtain the similarity degree between the two spectra according to the set of peak angles, the peak change difference and the difference in the peak sequence.

[0065] After screening out the characteristic segments in the target spectrum, the characteristic segments reflect the chemical substances in the powder. When comparing two different powders, the similarity measurement of the two powders will be more accurate. However, the data in the characteristic segments only shows the change in magnitude of the intensity. In the target spectrum, it is not enough to accurately measure only based on the magnitude of the intensity at the diffraction angle. Further judgment is needed by combining the change trend of the corresponding peaks and the size of the peaks. Therefore, when accurately judging the similarity between two different spectra, the change of the peaks also needs to be measured. When measuring the change of the peaks, the increasing and decreasing trends on both sides of the peak, and the size of the peak (which can be measured by the area of the peak) are the main means to measure the peak characteristics.

[0066] For a characteristic segment, with the intensity value within the segment as the ordinate and the diffraction angle as the abscissa, all data points of the characteristic segment are subjected to polynomial fitting to obtain the fitting curve of the characteristic segment. Polynomial fitting is a well-known technology and will not be elaborated further here. The function of the fitting curve is differentiated, and the points where the derivative is 0 are denoted as extreme points. Whether an extreme point is a peak point is determined according to the positive and negative properties on the left and right sides of the extreme point. If the adjacent point on the left side of the extreme point is positive and the adjacent point on the right side is negative, then this extreme point is a peak point. The intensities corresponding to all adjacent points with positive derivatives on the left side of the peak point form an increasing sequence, and the intensities corresponding to all adjacent points with negative derivatives on the right side of the peak point form a decreasing sequence. Thus, for each peak point, an increasing sequence and a decreasing sequence are obtained.

[0067] For each increasing sequence and decreasing sequence, the intensity value of each element in the sequence and its corresponding diffraction angle are taken as an element point. The fitting of all element points of the increasing sequence and the decreasing sequence is performed by linear fitting and polynomial fitting respectively to obtain the fitting straight line and fitting curve of the increasing sequence, and the fitting straight line and fitting curve of the decreasing sequence. The fitting straight line and fitting curve obtained at this time are respectively denoted as the target fitting straight line and the target fitting curve. Linear fitting and polynomial fitting are well-known technologies and will not be elaborated specifically here.

[0068] When calculating the similarity between two spectra, first, all characteristic segments in each spectrum are obtained, the intersection of all characteristic segments in the two spectra is obtained, and the peaks of the characteristic segments of each spectrum are obtained. The set formed by the diffraction angles corresponding to all the peaks is denoted as the peak angle set.

[0069] For different spectra corresponding to two powders, the peak change differences corresponding to the peaks are obtained through the differences in the slopes of the increasing sequences, the differences in the slopes of the decreasing sequences, and the differences in the fitting curves of the peaks corresponding to the same diffraction angle. The expression is:

[0070] , where is the slope ratio of the target fitting straight line of the t-th monotonic sequence of the peak at the -th diffraction angle of the two spectra, is the absolute value of the difference in the integral area of the target fitting curve of the t-th monotonic sequence of the peak at the -th diffraction angle of the two spectra, takes values of 1 and 2, corresponding to the increasing sequence and the decreasing sequence of the peak respectively, represents the peak change difference corresponding to the peak at the -th diffraction angle.

[0071] If the intersection of the peak angle sets corresponding to two spectra is an empty set, then the similarity degree of the two spectra is set to 0. If the intersection of the peak angle sets corresponding to two spectra is not an empty set, the similarity degree between the two spectra is obtained based on the differences in the peak sequences of all characteristic segments of the two spectra, the intersection-union ratio of the peak angle sets, and the differences in the peak variations of all peaks in the intersection of the peak angle sets. The expression is as follows:

[0072] , represents the cosine angle between the sequence formed by the peak sequences of all characteristic segments of the spectrum of powder u and the sequence formed by the peak sequences of all characteristic segments of the spectrum of powder v. represents the intersection of the peak angle sets of powder u and powder v. represents the th difference in the peak variation corresponding to the diffraction angle of the peak. represents the intersection-union ratio of the peak angle sets of powder u and powder v. is a tuning parameter coefficient to avoid a zero denominator, taking an empirical value of 1. represents the similarity degree of the spectra corresponding to powder u and powder v.

[0073] It can be understood that when there is no overlap in the diffraction angles corresponding to the peaks of the characteristic segments in the spectra of two powders, it means that the two spectra must be dissimilar, so the similarity degree of the two spectra is 0. When the components and contents in the two powders are closer, the diffraction angles corresponding to the chemical substances, the changes in the peaks corresponding to the diffraction angles, and the peak intensities of the peaks are closer, that is, the intersection-union ratio is larger; the peak intensities of the peaks corresponding to each diffraction angle are closer, that is is smaller; the changes in the peaks corresponding to the diffraction angles are closer, and the monotonicity change speeds on both sides of the peak are close, that is, the slopes of the fitting lines are close, then is larger, and the curves on both sides of the peak are closer, and the peak sizes are closer, then is smaller, so is smaller; thus, when the components and contents in the two powders are closer, is larger. On the contrary, when the component differences or content differences in the two powders are large, there will be large differences in the peak sizes and the monotonicity change situations on both sides, and the of the two spectra is smaller, and the greater the difference, is smaller.

[0074] So far, the similarity degree of the spectra of the two powders has been obtained.

[0075] Step S004: Collect multiple standard solutions, fit a curve equation based on the similarity degree of multiple standard solution spectra, and substitute the similarity degree between the measured powder spectrum and the standard solution spectra into the equation to determine the content of chemical substances in the measured powder.

[0076] Collect the residual alkali solutions of the cathode materials for times, take these residual alkali solutions as standard solutions, and use ion chromatography to measure the residual alkali, obtaining the residual alkali content in each residual alkali solution, i.e., the content of different chemical substances. In this embodiment take the empirical value of 20. It should be noted that the value should be greater than the number of types of chemical substances in the residual alkali solution. The use of ion chromatography to measure the residual alkali is a well-known technology and will not be elaborated here. It should be noted that ion chromatography has higher detection accuracy compared to potentiometric titration. However, since ion chromatography usually takes a long time to complete one analysis, requires cumbersome pretreatment of the test solution before detection, and has high requirements for data reproducibility, strict control of the detection environment is needed, thus limiting its wide application.

[0077] After that, process the standard solutions to obtain the spectra of the standard solutions. Then, combine the standard solutions in pairs, calculate the similarity degree between the spectra of any two standard solutions, take all the similarity degrees as the dependent variables, and the differences in the contents of various chemical substances in the corresponding standard solutions as the independent variables. Use multiple non-linear regression to perform non-linear output fitting of the curve equation, which is called the residual alkali difference curve. Multiple non-linear regression is a well-known technology and will not be elaborated here. Finally, calculate the similarity degree between the spectrum of the measured powder and the spectra of all standard solutions, substitute the similarity degree into the residual alkali difference curve, and obtain the content of chemical substances in the measured powder by solving the system of equations. The system of equations is as follows:

[0078]

[0079] where are respectively the contents of the 1st to qth chemical substances in the measured powder, , , …, are respectively the similarity degrees between the spectra of standard solution 1, standard solution 2, standard solution and the spectrum of the measured powder, is the residual alkali difference curve function, is the content of the hth chemical substance in the th standard solution, , , .

[0080] Through the above method, more accurate measurement of the residual alkali in the cathode material of the sodium-ion battery can be achieved. Moreover, since the same residual alkali difference curve is used for measurements in different times and a fixed standard solution is used, the results of multiple residual alkali measurements are relatively consistent, thereby improving the accuracy of the residual alkali measurement.

[0081] It should be noted that the above-described 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 foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features. And these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the various embodiments of the present application, and should all be included within the protection scope of the present application.

[0082] Each embodiment in this specification is described in a progressive manner. The same or similar parts among the various embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A method for determining residual alkali in composite phase sodium ion battery cathode materials, characterized in that: The method comprises the following steps: Use XRD analysis to obtain the target spectrum of the measured powder; The curve in the target spectrum is segmented, and the peaks in the curve segments are sorted according to the size of the diffraction angle to obtain the peak sequence of each segment; the prominence of the peak sequence is obtained according to the intensity difference between the elements in the peak sequence; the intensity characteristic coefficient of the curve segment corresponding to the peak sequence is obtained according to the coefficient of variation of the peak sequence, the difference in the prominence of the peak sequence and the other peak sequences, and the number of peak sequences; the curve segment is screened according to the size of the intensity characteristic coefficient to obtain the characteristic segment; Obtain the peak points in the characteristic segment, and obtain the increasing sequence and decreasing sequence of the peak points according to the intensity values ​​of the points adjacent to the peak points; fit the increasing sequence and the decreasing sequence to obtain the fitting straight line and the fitting curve of the corresponding sequences respectively; determine the peak angle set according to the peak of the characteristic segment of the spectrum; obtain the peak change difference corresponding to the peak according to the difference in the increasing sequence slope, the difference in the decreasing sequence slope and the difference in the fitting curve of the peak corresponding to the same diffraction angle of different spectra; determine whether the similarity is 0 according to the intersection of the peak angle sets of the two spectra, and obtain the similarity between the two spectra according to the difference in the peak sequences of all characteristic segments of the two spectra, the intersection-over-intersection ratio of the peak angle sets and the peak change difference of all peaks in the intersection of the peak angle sets; Collect standard solutions multiple times, obtain the spectra of the standard solutions and the contents of different chemical substances, and construct a fitting curve equation based on the similarity of the spectra between the standard solutions and the contents of the chemical substances; bring the similarity between the spectra of the test powder and the spectra of the standard solutions into the fitting curve equation to form an equation group to calculate the contents of multiple chemical substances in the test powder and complete the residual alkali determination; The method for constructing the fitting curve equation is: Acquire the spectra of multiple standard solutions, combine the standard solutions in pairs, calculate the similarity between the spectra of any two standard solutions, take all the similarities as dependent variables, and the difference in the content of each chemical substance in the corresponding standard solution as the independent variable, use multivariate nonlinear regression, perform nonlinear output fitting curve equation, and record the fitting curve equation as the residual alkali difference curve.

2. The residual alkali determination method for composite phase sodium ion battery positive electrode material according to claim 1, characterized in that: The method for obtaining the peak sequence is: The curve in the target spectrum is divided into several curve segments, and the peak data in each segment is extracted. According to the order of the diffraction angles corresponding to the peaks, the peak sequence of each segment is constructed, that is, each curve segment corresponds to a peak sequence.

3. The residual alkali determination method for composite phase sodium ion battery positive electrode material according to claim 1, characterized in that: The method for obtaining the prominence of the peak sequence according to the intensity difference between elements in the peak sequence is: The prominence of the peak sequence is positively correlated with the intensity difference between elements.

4. The residual alkali determination method for composite phase sodium ion battery positive electrode material according to claim 1, characterized in that: The method for obtaining the intensity characteristic coefficient of the curve segment corresponding to the peak sequence according to the coefficient of variation of the peak sequence, the difference in prominence between the peak sequence and other peak sequences, and the number of peak sequences is: The intensity characteristic coefficient of the curve segment corresponding to the peak sequence is positively correlated with the coefficient of variation of the peak sequence and the difference in prominence between the peak sequence and other peak sequences, and is negatively correlated with the number of peak sequences.

5. The residual alkali determination method for composite phase sodium ion battery positive electrode material according to claim 1, characterized in that: The method for obtaining the peak point in the characteristic segment and obtaining the increasing sequence and the decreasing sequence of the peak point according to the intensity values ​​of the points adjacent to the peak point is: Perform polynomial fitting on all data points of the feature segment to obtain the fitting curve of the feature segment, take derivative of the function of the fitting curve to obtain the extreme points, and select the peak points in the extreme points according to the positivity on the left and right sides of the extreme points; the intensity values ​​corresponding to all adjacent points on the left side of the peak point with positive derivatives form an increasing sequence, and the intensity values ​​corresponding to all adjacent points on the right side of the peak point with negative derivatives form a decreasing sequence.

6. The residual alkali determination method for composite phase sodium ion battery positive electrode material according to claim 1, characterized in that: The method for determining the peak angle set according to the peak value of the characteristic segment of the spectrum is: The peak value of each spectrum feature segment is obtained, and the set of diffraction angles corresponding to all peak values ​​is recorded as the peak angle set.

7. The residual alkali determination method for composite phase sodium ion battery positive electrode material according to claim 1, characterized in that: The method for obtaining the peak change difference corresponding to the peak value according to the difference in the slope of the increasing sequence, the difference in the slope of the decreasing sequence and the difference in the fitting curve of the peak value corresponding to the same diffraction angle of different spectra is: ,in For the two graphs in The slope ratio of the fitting straight line of the t-th monotonic sequence of the peak at the diffraction angle is, For the two graphs in The absolute value of the difference in the integrated area of ​​the fitting curve of the t-th monotonic sequence of the peak at the diffraction angle, The values ​​of 1 and 2 correspond to the increasing sequence and decreasing sequence of the peaks respectively. Indicates The difference in the peak change of the peak corresponding to each diffraction angle.

8. The residual alkali determination method for composite phase sodium ion battery positive electrode material according to claim 1, characterized in that: The method for determining whether the similarity is 0 according to the intersection of the peak angle sets of the two spectra, and obtaining the similarity between the two spectra according to the difference of the peak sequences of all feature segments of the two spectra, the intersection-over-intersection ratio of the peak angle sets, and the difference of the peak changes of all peaks in the intersection of the peak angle sets is: If the intersection of the peak angle sets corresponding to the two spectra is an empty set, the similarity of the two spectra is set to 0; If the intersection of the peak angle sets corresponding to the two spectra is not an empty set, the expression of the similarity between the two spectra is: , represents the cosine angle between the sequence of peaks of all characteristic segments of the spectrum of powder u and the sequence of peaks of all characteristic segments of the spectrum of powder v, represents the intersection of the peak angle sets of powder u and powder v, Indicates The difference in peak change corresponding to the diffraction angle is represents the intersection-over-combination ratio of the peak angle sets of powder u and powder v, is the preset tuning coefficient, Indicates the similarity between the spectra corresponding to powder u and powder v.

9. The residual alkali determination method for composite phase sodium ion battery positive electrode material according to claim 1, characterized in that: The method of bringing the similarity between the spectrum of the measured powder and the spectrum of the standard solution into the fitting curve equation to form an equation group to calculate the content of multiple chemical substances in the measured powder is: in The contents of the first to the qth chemical substances in the powder are measured respectively. , , …, They are standard solution 1, standard solution 2, and standard solution The similarity between the spectrum of the measured powder and the spectrum of the measured powder, is the residual alkali difference curve function, For the The content of the hth chemical substance in a standard solution, , , .

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