Method and equipment for determining trace metal content in micro-powder lithium carbonate

Abstract

The invention relates to the technical field of metal content determination, in particular to a method and equipment for determining the content of trace metal in micro-powder lithium carbonate, and the method comprises the following steps: screening out a characteristic wavelength from all specific wavelengths of each to-be-determined trace metal element based on wavelength difference and spectral intensity difference between different specific wavelengths; analyzing the wavelength difference and the spectral intensity difference between each non-specific wavelength and all other non-specific wavelengths, counting the frequency of the spectral intensity corresponding to each non-specific wavelength in the spectrum, and determining the baseline interference degree to screen the baseline interference wavelength; and correcting the spectral intensity based on the spectral intensity and the baseline interference degree of all the baseline interference wavelengths so as to measure the content of each trace metal element to be measured in the micro-powder lithium carbonate. According to the method, by screening the characteristic wavelength and adaptively deducting the background noise, the accuracy and reliability of measuring the content of the trace metal in the micro-powder lithium carbonate are improved.

Description

Technical Field

[0001] This application relates to the field of metal content determination technology, specifically to a method and equipment for determining trace metal content in micronized lithium carbonate. Background Technology

[0002] Micronized lithium carbonate, a key precursor for the core cathode material of new energy batteries, directly determines the battery's energy density, cycle life, and safety through its purity. During the production process, the presence of trace metallic impurities such as Fe, Cu, Zn, Ni, Cr, and Co, even in extremely low concentrations, can trigger internal side reactions, leading to serious safety hazards such as capacity decay and thermal runaway. Therefore, high-precision and high-reliability quantitative analysis of these trace metallic elements is a crucial control step in ensuring the quality and performance of lithium battery materials.

[0003] In the determination of trace metal content in micronized lithium carbonate, the commonly used spectroscopic techniques are inductively coupled plasma atomic emission spectrometry (ICP-AES) and mass spectrometry (ICP-MS). However, their inherent limitations restrict the accuracy of trace metal content determination. These inherent limitations are manifested in two aspects: first, the emission lines of different elements may overlap, causing peak interference; second, baseline interference such as banded spectra and background noise is difficult to be effectively corrected. These two problems together lead to deviations in the determination results of key trace metals such as Fe, Cu, and Zn. Not only can they not accurately reflect their true concentration, but imperfect baseline correction will also introduce additional errors, reducing the accuracy and reliability of trace metal content determination in micronized lithium carbonate. Summary of the Invention

[0004] To address the aforementioned technical problems, the purpose of this application is to provide a method and apparatus for determining the trace metal content in micronized lithium carbonate. The specific technical solution adopted is as follows: In a first aspect, embodiments of this application provide a method for determining the trace metal content in micronized lithium carbonate, the method comprising the following steps: The spectrum of micronized lithium carbonate and the spectral intensity of each trace metal element to be measured at all specific wavelengths are obtained, wherein the specific wavelengths include the dominant wavelength and the sub-wavelengths; Based on the difference in spectral intensity of each trace metal element under test at any secondary wavelength compared to the main wavelength, the wavelength difference between each secondary wavelength and all other secondary wavelengths, and the average distribution of the spectral intensity of each trace metal element under test at all secondary wavelengths, the characteristic degree of each trace metal element under test at any secondary wavelength is determined. Based on the difference between the spectral intensity of each trace metal element under any secondary wavelength and all other secondary wavelengths, the characteristic degree of each trace metal element under any secondary wavelength is optimized. Combined with the optimized characteristic degree of each trace metal element under the main wavelength, characteristic wavelengths are screened from all specific wavelengths of each trace metal element under the test. By analyzing the wavelength and spectral intensity differences between each non-specific wavelength and all other non-specific wavelengths, and by counting the frequency of the spectral intensity corresponding to each non-specific wavelength in the spectrum, the baseline interference degree of each non-specific wavelength is determined, so as to screen out the baseline interference wavelengths from all non-specific wavelengths; based on the spectral intensity and baseline interference degree of all baseline interference wavelengths, the spectral intensity of each trace metal element to be measured at the characteristic wavelength is corrected. The content of each trace metal element in micronized lithium carbonate was determined based on the corrected spectral intensity.

[0005] Preferably, the expression for the characteristic degree of each trace metal element to be measured at any wavelength is: In the formula, This represents the characteristic degree of the i-th trace metal element to be measured at the subwavelength j; This represents the judgment factor obtained based on the difference between the spectral intensity of the i-th trace metal element to be measured at the secondary wavelength j and the spectral intensity at the main wavelength j; The normalized value represents the minimum wavelength difference between the secondary wavelength j of the i-th trace metal element in the spectrum of micronized lithium carbonate and all specific wavelengths of the n-th trace metal element among all trace metal elements other than the i-th trace metal element. The mean normalized result of the spectral intensity of the nth trace metal element among all trace metal elements other than the i-th trace metal element to be measured at all specific wavelengths in the spectrum of micronized lithium carbonate. represents the number of all trace metal elements except the i-th trace metal element in the spectrum of micronized lithium carbonate; norm[ ] represents the normalization function.

[0006] Preferably, optimizing the characteristic of each trace metal element to be measured at any wavelength includes: Optimized characteristic of the i-th trace metal element to be measured at subwavelength j The expression is: In the formula, The characteristic of the i-th trace metal element to be measured in the spectrum of micronized lithium carbonate at the sub-wavelength j; The result represents the ratio of the spectral intensity of the i-th trace metal element to be measured at the secondary wavelength j to the spectral intensity at the upper secondary wavelength m within the spectrum of micronized lithium carbonate. This represents the ratio of the spectral intensity of the i-th trace metal element to the spectral intensity at the secondary wavelength j to the spectral intensity at the upper secondary wavelength m, obtained from the atomic emission spectroscopy database. The characteristic of the i-th trace metal element in the spectrum of micronized lithium carbonate at the secondary wavelength m is represented. This represents the number of all subwavelengths of the i-th trace metal element to be measured within the spectrum of micronized lithium carbonate.

[0007] Preferably, the characteristic wavelength is a specific wavelength corresponding to the maximum optimized characteristic degree for each trace metal element to be measured.

[0008] Preferably, the method for determining the baseline interference degree of each non-specific wavelength is as follows: The intensity similarity of each non-specific wavelength is determined by analyzing the wavelength differences and spectral intensity differences between each non-specific wavelength and all other non-specific wavelengths. The baseline interference of each non-specific wavelength is the result of positive fusion of the frequency of occurrence of the corresponding spectral intensity in the spectrum and the intensity similarity of each non-specific wavelength.

[0009] Preferably, the method for determining the intensity similarity of each non-specific wavelength is as follows: Within the spectrum of micronized lithium carbonate, the difference in spectral intensity between each non-specific wavelength and any other non-specific wavelength is calculated as the ratio of the wavelength distance between them, and this result is denoted as the difference characteristic value between each non-specific wavelength and any other non-specific wavelength. Calculate the sum of the difference characteristic values ​​between each non-specific wavelength and all other non-specific wavelengths. The intensity similarity of each non-specific wavelength is negatively correlated with the sum.

[0010] Preferably, the step of filtering out baseline interference wavelengths from all non-specific wavelengths includes: The mean of the baseline interference of all non-specific wavelengths in the spectrum of micronized lithium carbonate is used as the segmentation threshold, and non-specific wavelengths with baseline interference greater than the segmentation threshold are used as the baseline interference wavelengths.

[0011] Preferably, the correction of the spectral intensity of each trace metal element to be measured at a characteristic wavelength includes: The corrected spectral intensity of the i-th trace metal element in the spectrum of micronized lithium carbonate at the characteristic wavelength. The expression is: In the formula, The intensity of the i-th trace metal element to be measured in the spectrum of micronized lithium carbonate is represented at the characteristic wavelength. , The values ​​represent the spectral intensity and baseline interference degree at the baseline interference wavelength z in the spectrum of micronized lithium carbonate, respectively. This represents the spectral intensity of all baseline interference wavelengths within the spectrum of micronized lithium carbonate. The optimized characteristic degree of the i-th trace metal element to be measured in the spectrum of micronized lithium carbonate at the characteristic wavelength.

[0012] Preferably, the determination of the content of each trace metal element to be tested in the micronized lithium carbonate includes: Obtain the concentration-spectral intensity curve equation for each trace metal element to be measured; The concentration of each trace metal element to be measured is obtained by substituting the spectral intensity of each element at a characteristic wavelength into the concentration-spectral intensity curve equation. Secondly, embodiments of this application also provide a device for determining the trace metal content in micronized lithium carbonate, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above-described methods for determining the trace metal content in micronized lithium carbonate.

[0013] This application has at least the following beneficial effects: This application first evaluates the sensitivity of a wavelength based on the intensity relationship between the secondary wavelength and the primary wavelength. It then considers the spectral distance of this wavelength from all interfering elements and the overall intensity level of the interfering elements to construct a characteristic degree, quantifying the purity of the spectral environment. This helps identify characteristic wavelengths that are both sensitive and minimally affected by spectral line overlap, overcoming the problem of decreased accuracy and reliability in trace metal element determination caused by spectral line interference in traditional methods. Furthermore, this application optimizes the characteristic degree by quantifying the sensitivity of the spectral line itself and the purity of the spectral environment. Based on the optimized characteristic degree, it selects characteristic wavelengths that are both sensitive and minimally affected by interference, effectively overcoming the problem of spectral line overlap and contributing to the accuracy and reliability of trace metal detection. Finally, this application analyzes the morphological phases of non-specific wavelengths... The baseline interference degree is constructed by similarity and intensity universality to identify and screen out the true baseline interference wavelengths. Using this baseline interference degree as a weight, and combined with the optimized characteristic degree of the characteristic wavelength itself, adaptive subtraction is performed. This accurately eliminates non-specific background noise while avoiding over-correction of reliable signals, ultimately obtaining highly pure spectral data that truly reflects elemental content, laying the foundation for the ultimate accuracy of subsequent quantitative analysis. Finally, this application uses standard solutions of known concentrations for calibration to construct a reliable quantitative relationship model between spectral intensity and elemental concentration. The corrected spectral intensity of the sample to be tested is then substituted into this model to determine the actual content of each trace metal element in micronized lithium carbonate, improving the accuracy and reliability of trace metal content determination in micronized lithium carbonate. Attached Figure Description

[0014] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 A flowchart illustrating the steps of a method for determining trace metal content in micronized lithium carbonate according to one embodiment of this application; Figure 2 This is a flowchart of the characteristic wavelength screening steps provided in one embodiment of this application. Detailed Implementation

[0016] To further illustrate the technical means and effects adopted by this application to achieve the intended purpose of the invention, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a method and apparatus for determining trace metal content in micronized lithium carbonate according to this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0017] Unless otherwise defined, 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 pertains.

[0018] The following description, in conjunction with the accompanying drawings, details the specific scheme of the method and equipment for determining the trace metal content in micronized lithium carbonate provided in this application.

[0019] Please see Figure 1 The document illustrates a flowchart of a method for determining trace metal content in micronized lithium carbonate according to an embodiment of this application. The method includes the following steps: Step S1: Obtain the spectrum of micronized lithium carbonate and the spectral intensity of each trace metal element to be measured at all specific wavelengths, wherein the specific wavelengths include the dominant wavelength and the sub-wavelength.

[0020] The clear sample solution, after complete digestion and dilution to a fixed volume of micronized lithium carbonate, is drawn in at a constant rate using a peristaltic pump. The solution enters an atomizer, where it is pulverized into extremely fine aerosols by a high-speed argon gas flow. The aerosols are then filtered through the atomization chamber to select the smallest droplets, which are then carried by a carrier gas into an ICP torch at a temperature of 6000-10000K. Under this high-temperature environment, the sample droplets are rapidly desolvated, evaporated, atomized, and further excited or ionized. When the excited atoms transition back to lower energy levels, they emit their respective inherent spectra. The mixed beam is collected by a lens group and dispersed by a grating spectral system according to wavelength. Finally, the intensity signal of each spectral line is precisely captured at a specific wavelength by an optical sensor (CID) and converted into an electrical signal. This yields the spectrum of micronized lithium carbonate and the spectral intensity of each trace metal element at all specific wavelengths. The horizontal axis of the spectrum represents wavelength, and the vertical axis represents spectral intensity. The specific wavelengths include a dominant wavelength and all sub-wavelengths.

[0021] Step S2: By comprehensively evaluating spectral line overlap, its own intensity distribution, and intensity difference with the main wavelength, the characteristic degree of each subwavelength is determined. Furthermore, the characteristic degree is optimized by using the intensity relationship between subwavelengths to obtain the optimized characteristic degree, so as to screen out characteristic wavelengths.

[0022] Atomic emission spectrometry (AES) is a key technique for determining trace metallic impurities (such as Fe, Cu, and Zn) in micronized lithium carbonate. Its principle is based on the quantization of atomic energy levels: in a high-temperature light source such as ICP, atoms are excited, and their outer electrons transition to higher energy levels; when the electrons return to lower energy levels, they release photons with specific energies. Since photon energy corresponds one-to-one with wavelength, each element emits a series of unique spectral lines with fixed wavelengths, like an element's "fingerprint." Among these spectral lines, the wavelength with the highest intensity and greatest sensitivity is defined as the dominant wavelength (e.g., the dominant wavelength for Fe is 238.204 nm), and the rest are secondary wavelengths. By detecting these characteristic spectral lines, qualitative and quantitative analysis of the target element can be achieved.

[0023] To determine whether a sample contains a specific trace metal, a threshold needs to be set. This threshold is obtained through a blank experiment: First, a blank solution without the trace metal to be measured is prepared and subjected to the same digestion and processing procedures as the real sample to assess background interference throughout the analysis process. Then, the blank solution is measured multiple times to obtain a set of spectral intensity data at the specific wavelength of the trace metal to be measured. The average value and standard deviation of this set of spectral intensity data are calculated. The average value of the spectral intensity at the characteristic wavelength in the blank solution plus three times the standard deviation is used as the threshold. Trace metals with spectral intensities lower than the threshold, as well as trace metals that are not present, do not require further analysis.

[0024] Because overlapping of spectral lines of different elements may occur during the spectral determination of micronized lithium carbonate samples, leading to low accuracy in trace metal content measurement, this embodiment adaptively obtains the characteristic wavelength of each trace metal based on the overlap of specific wavelengths of different trace metals in the micronized lithium carbonate sample. The flowchart of the characteristic wavelength screening steps provided in this embodiment is as follows. Figure 2 As shown, the specific screening process is as follows: S2.1 Based on the difference in spectral intensity between each trace metal element and the main wavelength at any secondary wavelength, the wavelength difference between each trace metal element and all other secondary wavelengths, and the average distribution of the spectral intensity of each trace metal element at all secondary wavelengths, determine the characteristic degree of each trace metal element at any secondary wavelength.

[0025] As one implementation method, in this embodiment, the characteristic of the i-th trace metal element to be measured at the secondary wavelength j is... The expression is: In the formula, This represents the judgment factor obtained based on the difference between the spectral intensity of the i-th trace metal element to be measured at the secondary wavelength j and the spectral intensity at the main wavelength j; The normalized value represents the minimum wavelength difference between the secondary wavelength j of the i-th trace metal element in the spectrum of micronized lithium carbonate and all specific wavelengths of the n-th trace metal element among all trace metal elements other than the i-th trace metal element. The mean normalized result of the spectral intensity of the nth trace metal element among all trace metal elements other than the i-th trace metal element to be measured at all specific wavelengths in the spectrum of micronized lithium carbonate. This represents the number of all trace metal elements except the i-th trace metal element in the spectrum of micronized lithium carbonate.

[0026] The specific process for determining the factor is as follows: if the spectral intensity of the i-th trace metal element to be measured at the secondary wavelength j is greater than or equal to the spectral intensity at the primary wavelength, then the difference between the spectral intensity of the i-th trace metal element to be measured at the secondary wavelength j and the spectral intensity at the primary wavelength is used as the determination factor for the i-th trace metal element to be measured at the secondary wavelength j; conversely, if the spectral intensity of the i-th trace metal element to be measured at the secondary wavelength j is less than the spectral intensity at the primary wavelength, then the spectral intensity of the i-th trace metal element to be measured at the secondary wavelength j is used as the determination factor for the i-th trace metal element to be measured at the secondary wavelength j.

[0027] It should be noted that there are many methods for measuring the differences between data. In this embodiment, the absolute difference between the spectral intensity of the i-th trace metal element at the secondary wavelength j and the spectral intensity at the main wavelength is divided by the spectral intensity at the main wavelength, and this is taken as the difference between the spectral intensity of the i-th trace metal element at the secondary wavelength j and the spectral intensity at the main wavelength. Similarly, the absolute difference between the secondary wavelength j of the i-th trace metal element in the spectrum of micronized lithium carbonate and all specific wavelengths of the n-th trace metal element among all trace metal elements other than the i-th trace metal element is taken as the difference between the secondary wavelength j of the i-th trace metal element in the spectrum of micronized lithium carbonate and all specific wavelengths of the n-th trace metal element among all trace metal elements other than the i-th trace metal element. In practical applications, as other implementation methods, the implementer may also use other methods such as the square or ratio of the difference to measure the differences between data, depending on the circumstances. This embodiment does not impose any special restrictions on the selection of methods for measuring the differences between data.

[0028] It should be noted that in this embodiment... The purpose of the "+1" is to prevent complete overlap between specific wavelengths.

[0029] It should be noted that, unless otherwise specified, all content in this embodiment involving the measurement of differences between data uses the method of calculating absolute differences, and the specifics will not be elaborated further.

[0030] Based on the eigenvalue of each trace metal element at any subwavelength, it can be understood that the eigenvalue assesses the purity and usability of the spectral intensity at a specific wavelength. If the discriminant factor of the i-th trace metal element at subwavelength j is larger, it indicates that subwavelength j is more sensitive to the i-th trace metal element and more effectively characterizes its content; therefore, the corresponding eigenvalue is also larger. Simultaneously, if the normalized value of the minimum wavelength difference between the subwavelength j of the i-th trace metal element and all specific wavelengths of the n-th trace metal element among all trace metal elements other than the i-th trace metal element is larger, it indicates that the i-th trace metal element is more sensitive to other trace metal elements. The farther apart the spectral lines of trace metal elements are in wavelength, the cleaner the spectral environment, the less likely the spectral intensity of the i-th trace metal element to be interfered with at the secondary wavelength j, and the higher the reliability of the spectral intensity. Therefore, the corresponding characteristic is greater. In addition, if the normalized mean of the spectral intensity of the n-th trace metal element at all specific wavelengths among all trace metal elements other than the i-th trace metal element in the spectrum of micronized lithium carbonate is smaller, it indicates that the content of the n-th trace metal element may be lower, and its ability to interfere with the spectral intensity of the i-th trace metal element is weaker. Therefore, the reliability of the spectral intensity of the i-th trace metal element at the secondary wavelength j is higher, and the corresponding characteristic is also greater. Conversely, if the judgment factor of the i-th trace metal element at the secondary wavelength j is smaller, it indicates that the secondary wavelength j is less responsive to the i-th trace metal element and less effective in characterizing its content. Therefore, the corresponding characteristic degree is also smaller. At the same time, if the minimum wavelength difference between the secondary wavelength j and the spectral lines of all other trace metal elements is smaller, it indicates that the wavelength is closer to the spectral lines of other elements, the spectral environment is more crowded, the spectral intensity is more likely to be interfered with, and the reliability is lower. Therefore, the corresponding characteristic degree is also smaller. In addition, if the average spectral intensity of any other trace metal element at all specific wavelengths is larger, it indicates that the content of the interfering element may be higher, and its potential interference ability is stronger, resulting in lower reliability of the spectral intensity of the i-th trace metal element at the secondary wavelength j. Therefore, the corresponding characteristic degree is also smaller.

[0031] Thus, this embodiment evaluates its sensitivity based on the intensity relationship between the secondary wavelength and the primary wavelength, and takes into account the spectral distance of this wavelength from all other interfering elements and the overall intensity level of the interfering elements to construct a characteristic degree and quantify the purity of the spectral environment. This helps to identify characteristic wavelengths that are both sensitive and least affected by spectral line overlap, thereby overcoming the problem of decreased accuracy caused by spectral line interference in traditional methods, and thus helping to improve the accuracy and reliability of trace metal element content measurement.

[0032] S2.2 Based on the difference between the spectral intensity of each trace metal element under any secondary wavelength and all other secondary wavelengths, optimize the characteristic degree of each trace metal element under any secondary wavelength, and combine it with the optimized characteristic degree of each trace metal element under the main wavelength to screen characteristic wavelengths from all specific wavelengths of each trace metal element.

[0033] The above steps can obtain the characteristic degree of each trace metal element under sub-wavelength. However, this characteristic degree is insufficient to accurately quantify the specific interference introduced by other elements in actual measurement. To overcome this limitation, this embodiment optimizes the characteristic degree of each trace metal element under any sub-wavelength based on the difference between the spectral intensity of each trace metal element under any sub-wavelength and all other sub-wavelengths. Combined with the optimized characteristic degree of each trace metal element under the main wavelength, characteristic wavelengths are screened from all specific wavelengths of each trace metal element under the test. The specific process is as follows: In this embodiment, firstly, based on the difference in spectral intensity between any secondary wavelength and all other secondary wavelengths for each trace metal element to be measured, the characteristic degree of each trace metal element to be measured at any secondary wavelength is optimized. Specifically: As one implementation method, in this embodiment, the optimized characteristic degree of the i-th trace metal element to be measured at the subwavelength j The expression is: In the formula, The characteristic of the i-th trace metal element to be measured in the spectrum of micronized lithium carbonate at the sub-wavelength j; The result represents the ratio of the spectral intensity of the i-th trace metal element to be measured at the secondary wavelength j to the spectral intensity at the upper secondary wavelength m within the spectrum of micronized lithium carbonate. This represents the ratio of the spectral intensity of the i-th trace metal element to the spectral intensity at the secondary wavelength j to the spectral intensity at the upper secondary wavelength m, obtained from the atomic emission spectroscopy database. The characteristic of the i-th trace metal element in the spectrum of micronized lithium carbonate at the secondary wavelength m is represented. This represents the number of all subwavelengths of the i-th trace metal element to be measured within the spectrum of micronized lithium carbonate.

[0034] The process of obtaining the spectral intensity of trace metal elements at a specific wavelength from an atomic emission spectroscopy database is a well-known technique and will not be described in detail here.

[0035] Based on the optimized eigenvalue of each trace metal element under any secondary wavelength, it can be understood that the optimized eigenvalue characterizes the comprehensive purity and reliability of the spectral intensity at a specific wavelength. The eigenvalue, as the basis for calculating the optimized eigenvalue, provides a preliminary assessment of the purity at a specific wavelength. Based on the eigenvalue, if the eigenvalue of the i-th trace metal element under secondary wavelength j in the spectrum of micronized lithium carbonate is larger, it indicates that the spectral intensity of the i-th trace metal element under secondary wavelength j is more reliable. Therefore, the corresponding optimized eigenvalue is also larger, and secondary wavelength j is more likely to be selected as the characteristic wavelength subsequently. Meanwhile, if... The larger the value of the characteristic of the i-th trace metal element under test at the secondary wavelength m in the spectrum of micronized lithium carbonate, the smaller the characteristic of the i-th trace metal element under test at the secondary wavelength m indicates that the spectral intensity of the i-th trace metal element under test at the secondary wavelength m is unreliable. Furthermore, the measured value of the spectral intensity of the i-th trace metal element under test at the secondary wavelength j deviates significantly from the theoretical expectation. This, on the contrary, proves that the spectral intensity at the secondary wavelength j is more reliable. Therefore, the secondary wavelength j is more likely to be selected as the characteristic wavelength in the future. Thus, the optimized characteristic of the i-th trace metal element under test at the secondary wavelength j should be increased. Conversely, if the characteristic degree of the i-th trace metal element to be measured at the sub-wavelength j is smaller, it indicates a lower initial reliability of its spectral intensity. Therefore, the corresponding optimized characteristic degree is also smaller, and the probability that the sub-wavelength j will be selected as the characteristic wavelength in the future decreases accordingly. At the same time, if the characteristic ratio deviation... The smaller the value of the subwavelength j, and the larger the eigenvalue of the corresponding subwavelength m, the more stable the spectral line intensity relationship within the entire element is, indicating that it has not been significantly disturbed. However, this does not provide a basis for the reliability of the subwavelength j; therefore, the optimized eigenvalue of the subwavelength j will not be improved as a result. Furthermore, if the eigenvalue deviation... The characteristic of the subwavelength j is very large, but the characteristic of the subwavelength m is also very large in comparison, indicating that a serious ratio distortion has occurred. This means that the problem is likely to lie in the subwavelength j itself. Therefore, its optimized characteristic should be significantly reduced, and the possibility of the subwavelength j being selected as the characteristic wavelength is also smaller, and the corresponding optimized characteristic will also be smaller. Furthermore, this embodiment obtains the optimized eigenvalue of each trace metal element under the main wavelength and combines it with the optimized eigenvalue under any secondary wavelength to screen characteristic wavelengths from all specific wavelengths of each trace metal element under the test. Specifically: Based on the method for calculating the characteristic degree of trace metal elements at the secondary wavelength, the characteristic degree of trace metal elements at the primary wavelength is calculated. Thus, the optimized characteristic degree of each trace metal element to be measured at the primary and secondary wavelengths is obtained, which means the optimized characteristic degree of each trace metal element to be measured at all specific wavelengths is obtained.

[0036] Furthermore, the specific wavelength corresponding to the maximum optimized characteristic degree for each trace metal element to be measured is used as the characteristic wavelength for subsequent determination of the content of the trace metal element to be measured. The maximum optimized characteristic degree is the maximum value of the optimized characteristic degree of each trace metal element under all specific wavelengths.

[0037] Thus, this embodiment optimizes the characteristic degree by quantifying the sensitivity of the spectral line itself and the purity of the spectral environment. Based on the optimized characteristic degree, it selects characteristic wavelengths that are both sensitive and least affected by interference, thereby effectively overcoming the problem of spectral line overlap and contributing to the accuracy and reliability of trace metal detection.

[0038] Step S3: By analyzing the wavelength differences and spectral intensity differences between each non-specific wavelength and all other non-specific wavelengths, and by counting the frequency of the spectral intensity corresponding to each non-specific wavelength in the spectrum, the baseline interference degree of each non-specific wavelength is determined, so as to screen out the baseline interference wavelengths from all non-specific wavelengths; based on the spectral intensity and baseline interference degree of all baseline interference wavelengths, the spectral intensity of each trace metal element to be measured at the characteristic wavelength is corrected.

[0039] After selecting the specific wavelength with the highest optimized characteristic for each trace metal as its characteristic wavelength, the interference of spectral line overlap between elements has been effectively overcome. However, the optimized characteristic mainly evaluates the mutual influence between trace metal elements, and cannot characterize the baseline interference caused by non-element-specific factors such as band spectra and background noise. Therefore, this embodiment analyzes the wavelength differences and spectral intensity differences between each non-specific wavelength and all other non-specific wavelengths, and counts the frequency of the spectral intensity corresponding to each non-specific wavelength in the spectrum to determine the baseline interference degree of each non-specific wavelength, so as to screen out the baseline interference wavelengths from all non-specific wavelengths. Based on the spectral intensity and baseline interference degree of all baseline interference wavelengths, the spectral intensity of each trace metal element to be measured at the characteristic wavelength is corrected, that is, this kind of baseline interference is corrected to ensure the purity of the spectrum. The specific process is as follows: In this embodiment, firstly, by analyzing the wavelength differences and spectral intensity differences between each non-specific wavelength and all other non-specific wavelengths, specifically: Within the spectrum of micronized lithium carbonate, the difference in spectral intensity between each non-specific wavelength and any other non-specific wavelength is calculated as the ratio of the wavelength distance between them, and this result is denoted as the difference characteristic value between each non-specific wavelength and any other non-specific wavelength. Calculate the sum of the difference characteristic values ​​between each non-specific wavelength and all other non-specific wavelengths. The intensity similarity of each non-specific wavelength is negatively correlated with the sum.

[0040] It should be noted that, in this embodiment, the non-specific wavelength is defined as a wavelength other than a specific wavelength and whose spectral intensity is not zero.

[0041] It should be understood that a negative correlation means that the dependent variable decreases as the independent variable increases, and the dependent variable increases as the independent variable decreases. It can be a subtraction relationship or a division relationship, etc., depending on the actual application. This application does not impose any special restrictions.

[0042] Preferably, as one implementation method, in this embodiment, the intensity similarity of each non-specific wavelength is taken as the value of an exponential function with the natural constant as the base and the negative of the sum of the difference characteristic values ​​between each non-specific wavelength and all other non-specific wavelengths as the independent variable. In practical applications, as other implementation methods, implementers may also use other methods such as reciprocals to measure negative correlations according to specific circumstances. This embodiment does not impose any special restrictions.

[0043] Based on the intensity similarity of each non-specific wavelength, it can be understood that the intensity similarity quantifies the similarity between the spectral intensity of the non-specific wavelength and the spectral intensity of the surrounding non-specific wavelengths, thereby determining whether the non-specific wavelength belongs to the baseline interference. If the difference in spectral intensity between the current non-specific wavelength and any other non-specific wavelength is greater, the corresponding intensity similarity is smaller, indicating that the spectral intensity of the current non-specific wavelength is more prominent in the spectrum and less likely to be a smooth baseline. Conversely, if the difference in spectral intensity between the current non-specific wavelength and any other non-specific wavelength is smaller, the corresponding intensity similarity is greater, indicating that the spectral intensity of the current non-specific wavelength is more flat in the spectrum and blends into the surrounding environment, and is more likely to be part of a smooth baseline. Meanwhile, the wavelength distance between the current non-specific wavelength and any other non-specific wavelength is used as a weighting factor. The smaller the wavelength distance between the current non-specific wavelength and any other non-specific wavelength, the closer the current non-specific wavelength is to the other non-specific wavelength, and the more valuable the other non-specific wavelengths are for determining whether the current non-specific wavelength is the baseline. Conversely, the larger the wavelength distance between the current non-specific wavelength and any other non-specific wavelength, the farther the current non-specific wavelength is to the other non-specific wavelength, and the less valuable the other non-specific wavelengths are for determining whether the current non-specific wavelength is the baseline.

[0044] Furthermore, this embodiment determines the baseline interference level of each non-specific wavelength based on the intensity similarity of each non-specific wavelength and by statistically analyzing the frequency of occurrence of the corresponding spectral intensity in the spectrum. This allows for the selection of baseline interference wavelengths from all non-specific wavelengths. Specifically: In this embodiment, the frequency of occurrence of the spectral intensity corresponding to each non-specific wavelength in the spectrum and the intensity similarity are positively fused to obtain the baseline interference degree of each non-specific wavelength.

[0045] It should be understood that positive fusion refers to combining two or more indicators through addition or multiplication to obtain a comprehensive indicator, thereby more comprehensively and accurately assessing a phenomenon or problem. This fusion method is not limited to simple arithmetic operations, but can also include more complex statistical models and analytical methods. Implementers can choose according to specific circumstances, and this embodiment does not impose any special restrictions.

[0046] Preferably, as one implementation method, in this embodiment, the product of the frequency of occurrence of the spectral intensity corresponding to each non-specific wavelength in the spectrum and the intensity similarity is used as the baseline interference degree of each non-specific wavelength; in practical applications, as other implementation methods, implementers may also adopt other positive fusion methods such as sum values ​​according to specific circumstances, and this embodiment does not impose any special restrictions.

[0047] Based on the baseline interference degree of each non-specific wavelength, it can be understood that the baseline interference degree is used to determine the probability that the non-specific wavelength belongs to the baseline interference. If the frequency of the spectral intensity corresponding to the current non-specific wavelength appears in the spectrum, it means that the spectral intensity corresponding to the current non-specific wavelength is ubiquitous in the spectrum and is a common background signal. Therefore, the probability that the current non-specific wavelength belongs to the baseline interference is greater, and the corresponding baseline interference degree is also greater. At the same time, if the intensity similarity of the current non-specific wavelength is greater, it means that the spectral intensity of the current non-specific wavelength is more similar to the spectral intensity of the surrounding wavelengths and the more like the baseline in shape. Therefore, the corresponding baseline interference degree is also greater. Conversely, if the frequency of the spectral intensity corresponding to the current non-specific wavelength in the spectrum is smaller, it indicates that the intensity value is rare and is more likely to be an isolated, real signal. Therefore, the possibility that the current non-specific wavelength belongs to baseline interference is smaller, and the corresponding baseline interference degree is also smaller. At the same time, if the intensity similarity of the current non-specific wavelength is smaller, it indicates that its spectral intensity is significantly different from the surrounding wavelengths, and its shape is more like an independent "peak" rather than a smooth baseline. Therefore, the corresponding baseline interference degree is also smaller.

[0048] Furthermore, in this embodiment, the mean value of the baseline interference of all non-specific wavelengths in the spectrum of micronized lithium carbonate is used as the segmentation threshold, and non-specific wavelengths with baseline interference greater than the segmentation threshold are used as baseline interference wavelengths.

[0049] Furthermore, this embodiment corrects the spectral intensity of each trace metal element at its characteristic wavelength based on the spectral intensity and baseline interference degree of all baseline interference wavelengths. Specifically: As one implementation method, in this embodiment, the spectral intensity of the i-th trace metal element to be measured in the spectrum of micronized lithium carbonate is corrected at the characteristic wavelength. The expression is: In the formula, The intensity of the i-th trace metal element to be measured in the spectrum of micronized lithium carbonate is represented at the characteristic wavelength. , The values ​​represent the spectral intensity and baseline interference degree at the baseline interference wavelength z in the spectrum of micronized lithium carbonate, respectively. This represents the spectral intensity of all baseline interference wavelengths within the spectrum of micronized lithium carbonate. The optimized characteristic degree of the i-th trace metal element to be measured in the spectrum of micronized lithium carbonate at the characteristic wavelength.

[0050] Based on the corrected spectral intensity of each trace metal element at its characteristic wavelength, it can be understood that during the spectral intensity correction process... This reflects the magnitude of background noise that needs to be extracted from the characteristic wavelength. This part doesn't simply average the intensities of all interfering wavelengths; instead, it uses their respective baseline interference levels as weights. This means that the spectral intensity of a wavelength deemed highly likely to interfere—that is, a wavelength with a higher baseline interference level—has greater weight in calculating the average interference. This indicates that the background environment of the characteristic wavelength of the i-th trace metal element being measured is noisier, requiring more noise to be removed, and thus resulting in a higher corrected spectral intensity. Simultaneously, if the optimized characteristic degree of the i-th trace metal element at the characteristic wavelength is smaller, it indicates that the characteristic wavelength itself still has some spectral line overlap issues. In this case, the confidence in the spectral intensity at the characteristic wavelength decreases, leading to a more significant baseline correction. Enlarge it to eliminate all potential interference as much as possible; Conversely, if The smaller the value, the "quieter" the background environment of the characteristic wavelength, the less background noise needs to be subtracted, and therefore the smaller the corresponding correction amount, resulting in a lower corrected spectral intensity. The closer it is to the original spectral intensity Meanwhile, if the optimized characteristic degree of the i-th trace metal element to be measured in the spectrum at the characteristic wavelength... The larger the value, the more reliable the selected characteristic wavelength is, and the less interference it is subjected to from spectral line overlap. In this case, the higher the confidence in its original spectral intensity, the more gentle the baseline correction will be to avoid over-correction and loss of the true spectral intensity.

[0051] Thus, this embodiment constructs a baseline interference degree by analyzing the morphological similarity and intensity universality of non-specific wavelengths, thereby identifying and screening out the true baseline interference wavelengths. Using the baseline interference degree as a weight, and combining it with the optimized characteristic degree of the characteristic wavelength itself, adaptive subtraction is performed. This not only accurately eliminates non-specific background noise, but also avoids over-correction of reliable signals, thereby ultimately obtaining highly pure spectral data that truly reflects the elemental content, laying the foundation for the ultimate accuracy of subsequent quantitative analysis.

[0052] Step S4: Based on the corrected spectral intensity, determine the content of each trace metal element in the micronized lithium carbonate.

[0053] Based on steps S2 and S3, the spectral intensity of the trace metal element to be measured was corrected. When obtaining the actual content of the trace metal element to be measured through the corrected spectral intensity, firstly, the concentration-spectral intensity curve equation of each trace metal element to be measured was obtained, that is, a quantitative relationship between spectral intensity and the concentration of trace metal element was established. Furthermore, based on the quantitative relationship, the content of each trace metal element to be measured in the micronized lithium carbonate was determined. The specific process is as follows: In this embodiment, firstly, a predetermined number of standard micronized lithium carbonate solutions with known concentrations of various trace metal elements to be tested are prepared. For example, for iron (Fe), different concentrations of iron are added when preparing the predetermined number of standard micronized lithium carbonate solutions with known iron concentrations, such as 0 ppb, 10 ppb, 20 ppb, 50 ppb, 100 ppb, ... concentrations of iron are added. In practical applications, the implementer can set the added concentration of various trace metal elements to be tested and the number of standard micronized lithium carbonate solutions prepared according to specific circumstances. This embodiment does not impose any special restrictions.

[0054] The preparation process of the standard micronized lithium carbonate solution is a well-known technology and will not be described in detail here.

[0055] Furthermore, following the method for obtaining the corrected spectral intensity, the corrected spectral intensities of various trace metal elements to be measured at characteristic wavelengths within the spectrum of the standard micro-powdered lithium carbonate solution are obtained. All concentrations of various trace metal elements to be measured within the spectrum of the standard micro-powdered lithium carbonate solution and their corresponding spectral intensities are fitted. The independent variable of the fitted curve equation is the concentration of each trace metal element to be measured, and the ordinate is the corrected spectral intensity corresponding to different concentrations of each trace metal element to be measured. The fitted curve equation for each trace metal element to be measured is obtained and is denoted as the concentration-spectral intensity curve equation for each trace metal element to be measured. The concentration of each trace metal element was obtained by substituting the spectral intensity of each trace metal element at a characteristic wavelength into the concentration-spectral intensity curve equation of each trace metal element in the spectrum of micronized lithium carbonate.

[0056] It should be noted that there are many commonly used fitting algorithms. In this embodiment, the least squares method is used to fit the spectral intensity and concentration to obtain the fitting curve equation. In practical applications, as other implementation methods, implementers may also use other fitting methods such as polynomial function fitting according to specific circumstances. This embodiment does not impose any special restrictions on the selection of fitting algorithms.

[0057] The least squares method is a well-known technique, and the specific process of using it to fit spectral intensity and concentration will not be elaborated here.

[0058] Thus, this embodiment uses standard solutions of known concentrations for calibration to construct a reliable quantitative relationship model between spectral intensity and elemental concentration. Finally, the corrected spectral intensity of the sample to be tested is substituted into this model to determine the actual content of each trace metal element in micronized lithium carbonate, thereby improving the accuracy and reliability of the determination of trace metal content in micronized lithium carbonate. Based on the same inventive concept as the above method, this application embodiment also provides a device for determining the trace metal content in micronized lithium carbonate, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the methods described above for determining the trace metal content in micronized lithium carbonate.

[0059] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments of this specification have been described above. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0060] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0061] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this application should be included within the protection scope of this application.

Claims

1. A method for determining the trace metal content in micronized lithium carbonate, characterized in that, The method includes the following steps: The spectrum of micronized lithium carbonate and the spectral intensity of each trace metal element to be measured at all specific wavelengths are obtained, wherein the specific wavelengths include the dominant wavelength and the sub-wavelengths; Based on the difference in spectral intensity of each trace metal element under test at any secondary wavelength compared to the main wavelength, the wavelength difference between each secondary wavelength and all other secondary wavelengths, and the average distribution of the spectral intensity of each trace metal element under test at all secondary wavelengths, the characteristic degree of each trace metal element under test at any secondary wavelength is determined. Based on the difference between the spectral intensity of each trace metal element under any secondary wavelength and all other secondary wavelengths, the characteristic degree of each trace metal element under any secondary wavelength is optimized. Combined with the optimized characteristic degree of each trace metal element under the main wavelength, characteristic wavelengths are screened from all specific wavelengths of each trace metal element under the test. By analyzing the wavelength and spectral intensity differences between each non-specific wavelength and all other non-specific wavelengths, and by counting the frequency of the spectral intensity corresponding to each non-specific wavelength in the spectrum, the baseline interference degree of each non-specific wavelength is determined, so as to screen out the baseline interference wavelengths from all non-specific wavelengths; based on the spectral intensity and baseline interference degree of all baseline interference wavelengths, the spectral intensity of each trace metal element to be measured at the characteristic wavelength is corrected. The content of each trace metal element in micronized lithium carbonate was determined based on the corrected spectral intensity.

2. The method for determining trace metal content in micronized lithium carbonate as described in claim 1, characterized in that, The expression for the characteristic degree of each trace metal element to be measured at any wavelength is as follows: In the formula, This represents the characteristic degree of the i-th trace metal element to be measured at the subwavelength j; This represents the judgment factor obtained based on the difference between the spectral intensity of the i-th trace metal element to be measured at the secondary wavelength j and the spectral intensity at the main wavelength j; The normalized value represents the minimum wavelength difference between the secondary wavelength j of the i-th trace metal element in the spectrum of micronized lithium carbonate and all specific wavelengths of the n-th trace metal element among all trace metal elements other than the i-th trace metal element. The mean normalized result of the spectral intensity of the nth trace metal element among all trace metal elements other than the i-th trace metal element to be measured at all specific wavelengths in the spectrum of micronized lithium carbonate. This represents the number of all trace metal elements except the i-th trace metal element in the spectrum of micronized lithium carbonate.

3. The method for determining trace metal content in micronized lithium carbonate as described in claim 1, characterized in that, The optimization of the characteristic of each trace metal element under test at any wavelength includes: Optimized characteristic of the i-th trace metal element to be measured at subwavelength j The expression is: In the formula, The characteristic of the i-th trace metal element to be measured in the spectrum of micronized lithium carbonate at the sub-wavelength j; The result represents the ratio of the spectral intensity of the i-th trace metal element to be measured at the secondary wavelength j to the spectral intensity at the upper secondary wavelength m within the spectrum of micronized lithium carbonate. This represents the ratio of the spectral intensity of the i-th trace metal element to the spectral intensity at the secondary wavelength j to the spectral intensity at the upper secondary wavelength m, obtained from the atomic emission spectroscopy database. The characteristic of the i-th trace metal element in the spectrum of micronized lithium carbonate at the secondary wavelength m is represented. represents the number of all subwavelengths of the i-th trace metal element to be measured in the spectrum of micronized lithium carbonate; norm[ ] represents the normalization function.

4. The method for determining trace metal content in micronized lithium carbonate as described in claim 1, characterized in that, The characteristic wavelength is a specific wavelength corresponding to the maximum optimized characteristic degree for each trace metal element to be measured.

5. The method for determining trace metal content in micronized lithium carbonate as described in claim 1, characterized in that, The method for determining the baseline interference level of each non-specific wavelength is as follows: The intensity similarity of each non-specific wavelength is determined by analyzing the wavelength differences and spectral intensity differences between each non-specific wavelength and all other non-specific wavelengths. The baseline interference of each non-specific wavelength is the result of positive fusion of the frequency of occurrence of the corresponding spectral intensity in the spectrum and the intensity similarity of each non-specific wavelength.

6. The method for determining trace metal content in micronized lithium carbonate as described in claim 5, characterized in that, The method for determining the intensity similarity of each non-specific wavelength is as follows: Within the spectrum of micronized lithium carbonate, the difference in spectral intensity between each non-specific wavelength and any other non-specific wavelength is calculated as the ratio of the wavelength distance between them, and this result is denoted as the difference characteristic value between each non-specific wavelength and any other non-specific wavelength. Calculate the sum of the difference characteristic values ​​between each non-specific wavelength and all other non-specific wavelengths. The intensity similarity of each non-specific wavelength is negatively correlated with the sum.

7. The method for determining trace metal content in micronized lithium carbonate as described in claim 1, characterized in that, The process of filtering out baseline interference wavelengths from all non-specific wavelengths includes: The mean of the baseline interference of all non-specific wavelengths in the spectrum of micronized lithium carbonate is used as the segmentation threshold, and non-specific wavelengths with baseline interference greater than the segmentation threshold are used as the baseline interference wavelengths.

8. The method for determining trace metal content in micronized lithium carbonate as described in claim 1, characterized in that, The correction of the spectral intensity of each trace metal element to be measured at a characteristic wavelength includes: The corrected spectral intensity of the i-th trace metal element in the spectrum of micronized lithium carbonate at the characteristic wavelength. The expression is: In the formula, The intensity of the i-th trace metal element to be measured in the spectrum of micronized lithium carbonate is represented at the characteristic wavelength. , The values ​​represent the spectral intensity and baseline interference degree at the baseline interference wavelength z in the spectrum of micronized lithium carbonate, respectively. This represents the spectral intensity of all baseline interference wavelengths within the spectrum of micronized lithium carbonate. The optimized characteristic degree of the i-th trace metal element to be measured in the spectrum of micronized lithium carbonate at the characteristic wavelength.

9. The method for determining trace metal content in micronized lithium carbonate as described in claim 1, characterized in that, The determination of the content of each trace metal element in the micronized lithium carbonate includes: Obtain the concentration-spectral intensity curve equation for each trace metal element to be measured; Substituting the spectral intensity of each trace metal element to be measured at a characteristic wavelength into the concentration-spectral intensity curve equation within the spectrum of micronized lithium carbonate, the concentration of each trace metal element to be measured is obtained.

10. A device for determining the trace metal content in micronized lithium carbonate, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method for determining the trace metal content in micronized lithium carbonate as described in any one of claims 1-9.

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