Residual alkali determination method applied to composite phase sodium ion battery positive electrode material

Abstract

The invention relates to the technical field of material detection, in particular to a residual alkali determination method applied to a composite phase sodium ion battery positive electrode material. The method comprises the following steps: acquiring a spectrum of measured powder and recording the spectrum as a target spectrum; segmenting a curve in the target map, and calculating an intensity characteristic coefficient of a curve segment according to the intensity difference of each segment of peak sequence and the number of the peak sequences; screening the curve segments according to the intensity characteristic coefficients to obtain characteristic segments; obtaining a peak change difference according to the difference of the progressively-increasing and progressively-decreasing sequence slopes on the left side and the right side of the peak point in the feature segment and the peak angles, and obtaining the similarity degree of the two maps according to the set of the peak angles, the peak change difference and the difference of the peak sequences; collecting standard solutions for multiple times, fitting a curvilinear equation through the similarity degrees of multiple standard solution maps, and substituting the similarity degrees of the measured powder maps and the standard solution maps into the content of the chemical substances in the measured powder. According to the invention, the accuracy of residual alkali determination is improved.

Description

Technical Field

[0001] The present application relates to the technical field of electrical variable measurement, and in particular to a residual alkali determination method for composite phase sodium ion battery positive electrode materials. Background Art

[0002] Sodium-ion batteries (SIBs) are considered to be one of the important candidates to replace lithium-ion batteries because of their abundant resources, low cost and similar working principles to lithium-ion batteries. However, the performance of sodium-ion batteries depends largely on the design and synthesis of their positive electrode materials. During the synthesis of positive electrode materials, some sodium salts will form alkaline substances on the surface of the material after sintering. Alkaline substances are easy to absorb water and moisture, which affects the processing performance. At the same time, decomposition under high voltage will also cause battery bloating. Therefore, how to effectively detect the residual alkali content in the positive electrode material has become one of the key issues. At present, the method for determining the residual alkali in the positive electrode material of sodium-ion batteries is mainly potentiometric titration. The working principle is acid-base neutralization reaction, which involves the judgment of pH values ​​at two potential mutation points. However, the existing technology often gives a threshold range of pH values ​​at the mutation point. Therefore, when the measurement is performed multiple times, the measurement results are unstable, which affects the stability of positive electrode material production.

[0003] The XRD spectrum is relatively stable and accurate in measuring the chemical substances in the solution. At the same time, when the content of the chemical substances in the solution changes, the XRD spectrum will also change, so it becomes one of the solutions to ensure the stability and accuracy of the residual alkali determination. According to the difference in the XRD spectrum between the solution to be tested and the standard solution, the residual alkali determination can be performed, while avoiding the problem of unstable results of multiple measurements. However, when using existing methods such as spectral angle algorithms to perform similarity comparisons on complex data, similarity measurements are often performed through the entire XRD spectrum, but the chemical substances in the solution will only affect the intensity of a specific diffraction angle, 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 the similarity judgment, and then affect the accuracy of the residual alkali determination. Therefore, a more accurate similarity comparison method is needed to ensure the accuracy and stability of the residual alkali determination. Summary of the invention

[0004] In order to solve the technical problem that useless curve fluctuations affect the accuracy of measurement, the present application provides a residual alkali determination method for composite phase sodium ion battery positive electrode materials, and the technical scheme adopted is as follows: The present application proposes a method for determining residual alkali in composite phase sodium ion battery positive electrode materials, the method comprising the following steps: The spectrum of the powder to be measured is obtained and recorded as the target spectrum; The curve in the target spectrum is segmented, and the peak sequence of each segment is obtained; 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 prominence between the peak sequence and 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 segmentation; 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; Standard solutions are collected multiple times to obtain the spectra of the standard solutions and the contents of different chemical substances. A fitting curve equation is constructed based on the similarity of the spectra between the standard solutions and the contents of the chemical substances. The similarity between the spectra of the test powder and the spectra of the standard solutions is substituted 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.

[0005] In the above scheme, the present application calculates the intensity characteristic coefficient according to the changing trend of the intensity of each diffraction angle in the XRD spectrum of the residual alkali powder, and the coefficient enhances the accuracy of feature extraction in the XRD spectrum, extracts the characteristic segmentation of the XRD spectrum, and then enhances the accuracy of the subsequent similarity measurement; and then calculates the similarity of the spectrum according to the changes on both sides of the peak in the characteristic segmentation of the two XRD spectrums and the peak characteristics, and the similarity improves the accuracy of the similarity measurement of the XRD spectrum, and then improves the accuracy of the residual alkali determination; finally, the curve fitting is performed by the content of the chemical substance in the standard solution, so as to enhance the stability of multiple residual alkali determinations. In this way, according to the characteristics that the change of the chemical substance in the residual alkali solution will cause the change of the XRD spectrum, the characteristic change of the XRD spectrum is used to measure the similarity between two different XRD spectra, and the accuracy of the similarity measurement is enhanced. Subsequently, by measuring the similarity of the XRD spectrum between the residual alkali solution and the standard solution, the content of each chemical substance in the solution to be measured is determined, thereby completing the determination of the residual alkali. This method enhances the accuracy of XRD pattern similarity measurement, thereby improving the accuracy of residual alkali determination. By comparing with standard solutions, the content of each chemical substance can be obtained, and the stability during multiple measurements is guaranteed, thereby ensuring the stability of battery positive electrode material production.

[0006] In one embodiment, the method of segmenting the curve in the target spectrum and obtaining the peak sequence of each segment 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, a peak sequence of each segment is constructed, that is, each curve segment corresponds to a peak sequence.

[0007] In one embodiment, 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.

[0008] 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 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.

[0009] In one embodiment, the method of obtaining the peak points in the characteristic segment and obtaining the increasing sequence and the decreasing sequence of the peak points according to the intensity values ​​of the points adjacent to the peak points 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.

[0010] In one embodiment, 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.

[0011] In one embodiment, the method for obtaining the peak change difference corresponding to the peak value 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 values ​​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.

[0012] In one embodiment, the method for determining whether the similarity is 0 based on the intersection of the peak angle sets of the two spectra, and obtaining the similarity between the two spectra based on the difference in the peak sequences of all feature segments of the two spectra, the intersection-over-intersection ratio of the peak angle sets, and the difference in the peak change 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 parameter adjustment factor to avoid the denominator being 0, Indicates the similarity between the spectra corresponding to powder u and powder v.

[0013] In one embodiment, the method of collecting multiple standard solutions, obtaining the spectra of the standard solutions and the contents of different chemical substances, and constructing a fitting curve equation according to the similarity of the spectra between the standard solutions and the contents of the chemical substances 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.

[0014] In one embodiment, 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:

[0015] 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 qth chemical substance in a standard solution, , , . BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 A flow chart of a method for determining residual alkali in a composite phase sodium ion battery positive electrode material provided in one embodiment of the present application. DETAILED DESCRIPTION

[0018] In order to further explain the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the following is a detailed description of the residual alkali determination method for composite phase sodium ion battery positive electrode materials proposed in the present application, its specific implementation method, structure, characteristics and effects as follows in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0019] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0020] Example of residual alkali determination method applied to composite phase sodium ion battery positive electrode material: The specific scheme of the residual alkali determination method for composite phase sodium ion battery positive electrode materials provided in the present application is described in detail below with reference to the accompanying drawings.

[0021] See also Figure 1 , which shows a flow chart of a residual alkali determination method for composite phase sodium ion battery positive electrode material provided by an embodiment of the present application, the method comprising the following steps: Step S001, obtaining a spectrum of the powder to be measured and recording it as a target spectrum.

[0022] Use anhydrous ethanol as a solvent to dissolve the residual alkali on the surface of the composite phase sodium ion battery positive electrode material, and take the filtrate as the test solution after filtering. The test solution is the residual alkali solution of the positive electrode material. Then place the test solution in an oil bath and stir until the solvent evaporates. The temperature of the oil bath is 60 The powder is called the test powder. Then, an XRD ray scanner is used to perform X-ray diffraction analysis (XRD) on the test powder to obtain an XRD spectrum, which is recorded as the target spectrum. In this embodiment, the radiation source is Cu and Ka, and the scanning range is 10~80 , the scanning speed is .

[0023] At this point, the target map is obtained.

[0024] Step S002, segment the curve in the target spectrum, calculate 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; and screen the curve segment according to the size of the intensity characteristic coefficient to obtain the characteristic segment.

[0025] When the traditional potentiometric titration method is used to detect residual alkali, the pH value at the mutation point cannot be accurately determined. Therefore, the residual alkali determination effect is closely related to the degree of error in the pH value. When performing multiple residual alkali determinations, the instability of the pH value at the mutation point also makes the results of residual alkali determinations in different batches unstable.

[0026] When the positive electrode material is manufactured using the same process, for two powders, although the amount of residual alkali may not be completely the same, the chemical substances therein are relatively close, and the position and peak intensity of each chemical substance in the target spectrum are relatively consistent. Therefore, the closer the target spectrum of the two powders is, the closer the chemical substances in the two powders are, that is, the closer the residual alkali of the two powders are.

[0027] Therefore, the spectral angle algorithm can be used to compare the two target spectra; however, the traditional spectral angle algorithm measures the similarity of complex data by measuring the overall similarity of the curve. However, in the target spectrum, the curve is always fluctuating, but only those diffraction angles and intensity combinations that correspond to chemical substances and have obvious fluctuations are significant for the detection of powder similarity, while the contribution of the remaining majority of fluctuations is small. If the overall curve is still used for similarity measurement, it will cause a large error in the result. Therefore, it is necessary to extract significant features in the target spectrum and use these features for similarity judgment to make the results more accurate.

[0028] When performing XRD analysis on powder, each chemical substance in the powder corresponds to a unique combination, which reflects the different intensities corresponding to different diffraction angles. The horizontal axis of the target spectrum is the diffraction angle, and the vertical axis is the intensity corresponding to different diffraction angles. The intensity pays more attention to the peak value in the target spectrum, so when extracting features in the target spectrum, it is necessary to give greater weight to the peak data. However, since the curve is always fluctuating in the entire target spectrum, not all peak values ​​are significant, so it is necessary to further screen the peak values ​​based on the changing characteristics of the peak values.

[0029] When performing XRD analysis on powders, each chemical substance in the powder will suddenly increase in intensity at certain diffraction angles, while the fluctuations at other positions on the curve are often smaller because the corresponding diffraction angles do not correspond to the chemical substances. Secondly, on the entire curve of the target spectrum, except for the increase in the intensity of the chemical substances at some specific diffraction angles, there are no corresponding chemical substances at most of the remaining diffraction angles, so the corresponding intensities are relatively close.

[0030] Divide the curves in the target map equally into In this embodiment, The value is 20. Extract the peak data in each segment, and construct the peak sequence of each segment according to the order of the diffraction angle corresponding to the peak, that is, each curve segment corresponds to a peak sequence.

[0031] First, for each peak sequence, the prominence of the peak sequence is obtained according to the intensity difference between the elements in the peak sequence.

[0032] The prominence of the peak sequence is positively correlated with the intensity difference between elements.

[0033] It should be noted that positive correlation means that when one variable increases, the other variable also increases, and the two variables change in the same direction. 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 actual application and this application does not impose any special restrictions.

[0034] Preferably, in this embodiment, the absolute values ​​of the differences in the intensities of all elements in the peak sequence are calculated, and the average of all the absolute values ​​of the differences is calculated as the prominence degree of the peak sequence.

[0035] Preferably, in another embodiment of the present application, the standard deviation of the intensity of all elements in the peak sequence is calculated, and the standard deviation is used as the prominence degree of the peak sequence.

[0036] 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 prominence between the peak sequence and other peak sequences, and the number of peak sequences.

[0037] 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.

[0038] It should be noted that negative correlation means that when one variable increases, the other variable decreases accordingly, and the two variables change in opposite directions. 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 application and this application does not impose any special restrictions.

[0039] Preferably, in this embodiment, the expression of the intensity characteristic coefficient is: ; It is The intensity characteristic coefficient of the curve segment corresponding to the peak sequence, It is Peak sequence The coefficient of variation, is the number of peak trains, It is The prominence degree in the peak sequence, It is The prominence degree in the peak sequence, Indicates A peak sequence.

[0040] Preferably, in another embodiment of the present application, the expression of the intensity characteristic coefficient is: , It is The intensity characteristic coefficient of the curve segment corresponding to the peak sequence, It is Peak sequence The coefficient of variation, is the number of peak trains, It is The prominence degree in the peak sequence, It is The prominence degree in the peak sequence, Indicates A peak sequence.

[0041] It is understandable that when When the segment contains the peak of the diffraction angle corresponding to the chemical substance, the peak will increase significantly, so that the difference in the curve segment increases relatively, that is, the coefficient of variation Secondly, on the curve, only the intensity at a specific diffraction angle is large, and the intensity at the remaining diffraction angles is relatively small, that is, the peak sequence of most segments is less prominent, so when the first When there is a significant increase in the peak value within a segment, the difference between the prominence of the peak sequence of this segment and the prominence of the peak sequences of the remaining segments is large; so when the first When the segment contains the peak of the diffraction angle corresponding to the chemical substance, the intensity characteristic coefficient Larger and The more severe the peak fluctuation within a segment, The larger the value is, the better the data changes in this section can reflect the chemical substances in the powder. When the segment does not contain the peak corresponding to the diffraction angle of the chemical substance, It is smaller, indicating that this segment contributes less to the measurement of chemical substances in the powder.

[0042] By the above method, the intensity characteristic coefficients of all curve segments are calculated, and then all curve segments are divided into two categories according to the intensity characteristic coefficients, and the curve segments of a category with a larger average intensity characteristic coefficient are used as the characteristic segmentation of the target spectrum. In the present embodiment, the intensity characteristic coefficients of all segments are used as input, the Otsu threshold segmentation algorithm is adopted, the segmentation threshold is input, and all segments with intensity characteristic coefficients greater than the segmentation threshold are marked as the characteristic segmentation of the target spectrum. The Otsu threshold segmentation algorithm is a well-known technology and will not be described in detail.

[0043] At this point, all feature segments of the target graph have been obtained.

[0044] Step S003, obtaining the peak change difference according to the difference in the slope of the increasing and decreasing sequences on the left and right sides of the peak point in the characteristic segment and the peak angle, and obtaining the similarity of the two spectra according to the set of peak angles, peak change differences and peak sequence differences.

[0045] After the characteristic segments in the target spectrum are screened out, 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 show the change in intensity. But in the target spectrum, the intensity at the diffraction angle alone is not enough to make an accurate measurement. It is necessary to combine the change trend of the corresponding peak and the size of the peak for further judgment. Therefore, to accurately judge the similarity between two different spectra, the change of the peak must also be measured. When measuring the change of the peak, 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 characteristics of the peak.

[0046] For a characteristic segment, the intensity value in the segment is the ordinate, and the diffraction angle is the abscissa. All data points of the characteristic segment are polynomially fitted to obtain the fitting curve of the characteristic segment. Polynomial fitting is a well-known technology and will not be elaborated on again. The function of the fitting curve is differentiated, and the point where the derivative is 0 is recorded as the extreme point. Whether the extreme point is a peak point is determined based on the positive and negative values ​​on the left and right sides of the extreme point. If the adjacent points on the left side of the extreme point are positive and the adjacent points on the right side are negative, then the extreme point is the peak point. The intensities corresponding to all adjacent points on the left side of the peak point with positive derivatives constitute an increasing sequence, and the intensities corresponding to all adjacent points on the right side of the peak point with negative derivatives constitute a decreasing sequence. Thus, for each peak point, an increasing sequence and a decreasing sequence are obtained.

[0047] 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, and all element points of the increasing sequence and the decreasing sequence are fitted 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, and the fitting straight line and fitting curve obtained at this time are recorded as the target fitting straight line and target fitting curve, respectively. Linear fitting and polynomial fitting are well-known technologies, and are not described in detail.

[0048] When calculating the similarity of two spectra, first obtain all feature segments in each spectrum, obtain the intersection of all feature segments in the two spectra, obtain the peak value of each spectrum feature segment, and record the set of diffraction angles corresponding to all peak values ​​as the peak angle set.

[0049] For different spectra corresponding to two powders, the peak change difference corresponding to the peak is obtained by the difference in the increasing sequence slope, the decreasing sequence slope and the fitting curve difference corresponding to the peak at the same diffraction angle. The expression is: ,in For the two graphs in The slope ratio of the target fitting straight line of the t-th monotonic sequence of the peak at the diffraction angle, For the two graphs in The absolute value of the difference in the integrated area of ​​the target 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.

[0050] 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 similarity between the two spectra is obtained according to the difference in the peak sequences of all feature segments of the two spectra, the intersection-over-intersection ratio of the peak angle sets, and the difference in the peak changes of all peaks in the intersection of the peak angle sets. The expression 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 parameter adjustment coefficient to avoid the denominator being 0, and takes the empirical value 1. Indicates the similarity between the spectra corresponding to powder u and powder v.

[0051] It can be understood that when the diffraction angles corresponding to the peaks of the characteristic segments in the spectra of the two powders do not overlap, it means that the two spectra must be dissimilar, so the similarity of the two spectra is 0. When the ingredients and contents of 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 and union ratio of the peak angle sets is 0. The larger the peak intensities of the peaks corresponding to the diffraction angles, the closer the peaks are. The smaller the diffraction angle, the closer the peak changes are, and the monotonic change speeds on both sides of the peak are close, that is, the slopes of the fitting lines are close. The larger the peak, the closer the curves on both sides of the peak are, and the closer the peak sizes are, then Smaller, so smaller; thus, when the ingredients and contents of the two powders are closer, On the contrary, when the difference in composition or content between the two powders is large, the size of the peak and the monotonic changes on both sides will be very different. The smaller the difference, the greater the The smaller.

[0052] At this point, the similarity of the spectra of the two powders was obtained.

[0053] Step S004, collecting multiple standard solutions, fitting a curve equation through the similarity of the spectra of multiple standard solutions, and bringing the similarity between the measured powder spectrum and the standard solution spectrum into the content of the measured powder chemical substance.

[0054] collection The residual alkaline solution of the secondary positive electrode material A residual alkali solution is used as a standard solution, and ion chromatography is used to determine the residual alkali to obtain the residual alkali content in each residual alkali solution, that is, the content of different chemical substances. Take the experience value 20, it should be noted that The value should be greater than the number of chemical species in the residual alkali solution. Ion chromatography is a well-known technique for determining residual alkali, and the details are not repeated here. It should be noted that ion chromatography has higher detection accuracy than potentiometric titration, but since ion chromatography usually takes a long time to complete an analysis, it is also necessary to perform cumbersome pretreatment of the detection solution before detection. At the same time, the requirements for data reproducibility are high, and the detection environment needs to be strictly controlled, which limits its wide application.

[0055] After that, the standard solution is processed to obtain the spectrum of the standard solution. Then, the standard solutions are combined in pairs, and the similarity between the spectra of any two standard solutions is calculated. All similarities are used as dependent variables, and the difference in the content of each chemical substance in the corresponding standard solution is used as an independent variable. Multivariate nonlinear regression is used to perform nonlinear output fitting curve equation, which is called the residual alkali difference curve. Multivariate nonlinear regression is a well-known technology and will not be described in detail. Finally, the similarity between the spectrum of the measured powder and the spectrum of all standard solutions is calculated, and the similarity is brought into the residual alkali difference curve. By solving the equation group, the content of the chemical substance in the measured powder is obtained. The equation group is as follows:

[0056] 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 qth chemical substance in a standard solution, , , .

[0057] Through the above method, a more accurate measurement of the residual alkali in the positive electrode material of the sodium ion battery can be achieved, and because the same residual alkali difference curve is used in different measurements, 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.

[0058] 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 aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

[0059] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced 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: The spectrum of the powder to be measured is obtained and recorded as the target spectrum; The curve in the target spectrum is segmented, and the peak sequence of each segment is obtained; 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 prominence between the peak sequence and 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 segmentation; 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; Standard solutions are collected multiple times to obtain the spectra of the standard solutions and the contents of different chemical substances, and a fitting curve equation is constructed according to the similarity of the spectra between the standard solutions and the contents of the chemical substances. The similarity between the spectrum of the test powder and the spectrum of the standard solution is substituted 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.

2. The residual alkali determination method for composite phase sodium ion battery positive electrode material according to claim 1, characterized in that: The method of segmenting the curve in the target spectrum and obtaining the peak sequence of each segment 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 collecting multiple standard solutions, obtaining the spectra of the standard solutions and the contents of different chemical substances, and constructing a fitting curve equation according to the similarity of the spectra between the standard solutions and the contents of the chemical substances is as follows: 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.

10. The residual alkali determination method for composite phase sodium ion battery positive electrode material according to claim 9, 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 qth chemical substance in a standard solution, , , .

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