A method for rapid screening of cosmetic consistency based on X-ray fluorescence spectroscopy

Abstract

The present invention discloses a method for rapid screening of cosmetic consistency based on X-ray fluorescence spectroscopy, comprising the following steps: (1) sampling and loading, setting instrument parameters, and irradiating the sample with X-rays to obtain an XRF fingerprint spectrum; (2) establishing an XRF fingerprint spectrum database of cosmetic standard samples; (3) performing similarity analysis of the XRF fingerprint spectrum of the sample to be tested and the standard product, including full-element XRF spectrum similarity analysis, background scattering spectrum similarity analysis, and XRF comprehensive similarity analysis; and (4) performing XRF consistency analysis of the sample to be tested and the standard product. The method of the present invention has accurate and rapid identification results, is time-saving and low-cost, and is particularly suitable for rapid identification scenarios required by on-site supervision at ports and markets.

Description

Technical Field

[0001] The present invention relates to the field of cosmetics, and in particular to a method for rapid screening of cosmetic consistency based on X-ray fluorescence spectroscopy. Background Art

[0002] With the rapid development of online e-commerce platforms, cosmetics are increasingly sold through a growing number of channels. E-commerce platforms are placing increasing emphasis on authenticity and quality control, placing high demands on testing efficiency and accuracy. To prevent counterfeit and inferior products from entering the market, rapid pre-warehouse identification is essential. Current technical methods for consistency identification are imperfect, require long testing cycles, and require samples to be sent to a laboratory for testing, which doesn't adequately address pre-warehouse identification challenges. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a method for rapid screening of cosmetic consistency based on X-ray fluorescence spectroscopy.

[0004] The present invention can quickly and conveniently identify counterfeit and inferior cosmetics through analysis of XRF scanning spectra. It avoids the shortcomings of long and cumbersome testing cycles and high testing environment requirements, and can help businesses conduct quality control of counterfeit and inferior products in real time.

[0005] The method of the present invention is based on the formula system and product-related characteristics of cosmetics, combined with XRF analysis means, and calculated through mathematical statistical algorithms to establish a multi-dimensional analysis method for the consistency quality of cosmetics.

[0006] A method for rapid screening of cosmetic consistency based on X-ray fluorescence spectroscopy comprises the following steps:

[0007] (1) Sampling and loading, setting instrument parameters, irradiating the sample with X-rays, and obtaining the XRF fingerprint spectrum;

[0008] (2) Establish a database of XRF fingerprints of cosmetic standard samples;

[0009] (3) XRF fingerprint similarity analysis between the sample to be tested and the standard, including full-element XRF spectrum similarity analysis, background scattering spectrum similarity analysis and XRF comprehensive similarity analysis;

[0010] (4) XRF consistency analysis of the sample to be tested and the standard.

[0011] The method for rapid screening of cosmetic consistency based on X-ray fluorescence spectroscopy of the present invention, wherein the sampling and loading process in step (1) comprises: fixing the test film to the bottom of the XRF sample cup and clamping it with the sample cup hoop;

[0012] When the cosmetic is a solid sample, a layer of the cosmetic sample is evenly applied on the test film inside the sample cup to completely cover the test film;

[0013] When the cosmetics are aqueous solutions and emulsions, directly put in a layer of cosmetic sample to completely cover the sample injection film and set aside.

[0014] The method for rapid screening of cosmetic consistency based on X-ray fluorescence spectroscopy of the present invention comprises:

[0015] Test conditions Voltage / KeV Current / uA Power / W Sampling time / s Detector dead time Low-Energy 15 350 5.25 6.44 30％ Mid-Energy 30 100 11 139.18 30％ Hig-Energy 70 180 12 74.26 30％

[0016] The instrument parameter settings in step (1) are shown in the table above.

[0017] The method for rapid screening of cosmetic consistency based on X-ray fluorescence spectroscopy of the present invention, wherein step (2) comprises the following steps:

[0018] According to the XRF fingerprint determination method studied in step (1), a cosmetics standard sample XRF fingerprint database is established;

[0019] Select no less than 10 batches of the same cosmetic samples and perform XRF analysis in different energy bands to obtain energy spectra and the content of each characteristic element;

[0020] The original XRF spectrum was Gaussian filtered, and the characteristic peak of the element with the highest count rate and the best goodness of fit in the FP algorithm was selected as the reference peak. The XRF software also obtained the characteristic peak count rates of other elements.

[0021] Selection and determination of fingerprint spectrum quantitative information parameters: a. Count rate of characteristic peak; b. Ratio of count rate of characteristic peak to count rate of reference peak; c. Shape and intensity decomposition of scattering peak.

[0022] In the method for rapid screening of cosmetic consistency based on X-ray fluorescence spectroscopy of the present invention, the full-element XRF spectrum similarity analysis in step (3) comprises the following steps:

[0023] Fingerprint similarity algorithm: The ratios of the count rates of each characteristic peak in an energy band of the XRF fingerprint to the reference peak r1, r2, r3, ..., rn form an n-dimensional space vector R1 = r1, r2, r3, ..., rn. Each sample contains three spectra of low energy, medium energy, and high energy, namely three space vectors R1, R2, and R3. The Pearson correlation coefficients of the corresponding energy band space vectors of the two samples are calculated respectively, and the three correlation coefficients are weighted according to the number of characteristic peaks in each energy band. The total correlation coefficient of the characteristic peaks is obtained by linear addition. The Pearson correlation coefficient is a centralized correlation calculation method, and its calculation formula is as follows:

[0024]

[0025] S: Pearson correlation coefficient;

[0026] Xi: the spatial vector R of the sample to be investigated;

[0027] Yi: space vector of the control spectrum;

[0028] The weighted calculation method for the total correlation coefficient of characteristic peaks is as follows:

[0029]

[0030] in, And C i is the number of characteristic peaks in this energy band.

[0031] In the method for rapid screening of cosmetic consistency based on X-ray fluorescence spectroscopy of the present invention, the background scattering spectrum similarity analysis in step (3) comprises the following steps:

[0032] The scattering peak is filtered by Savitzky-Golay, and the fitting formula is:

[0033]

[0034] Among them, a k Construct a polynomial for fitting the scattering peak, where n = -m, ...0, ...m, which is 2m+1 integers;

[0035] The fitted residuals are:

[0036]

[0037] Where x[i] is the vector representing the scattering peak to be input;

[0038] The filtering result is expressed as:

[0039] y[0]=p(0)=a0

[0040] To minimize ε, its partial derivatives with respect to each parameter should be 0, that is:

[0041]

[0042] Substitute and simplify to get:

[0043]

[0044] Introduce the matrix A={a ni}, construct matrix B = A T A, then:

[0045] Ba=AT Aa=A T X,

[0046] a=(A T A) -1 A T X=HX

[0047] Align the filtered scattering peaks of the control sample and the test sample according to the number of channels, and then perform principal component analysis on each scattering peak spectrum;

[0048] First, the original data is standardized to obtain the standardized matrix Z:

[0049]

[0050] i=1,2,…,p

[0051] j=1,2,…,n

[0052] where x ij represents n samples of p-dimensional vectors,

[0053] The correlation coefficient matrix R of the spectrum X is expressed as follows:

[0054]

[0055] in

[0056] According to the characteristic equation of R|R-λI p |=0 to obtain p characteristic roots, according to To determine the number of principal components m, the principal component vector retains more than 95% of the information of the original spectrum.

[0057] Solve the system of equations R b =λ j b gets the unit eigenvector The principal component vector is then expressed as:

[0058]

[0059] Among them U i That is the i-th principal component;

[0060] Will U ij By calculating the Pearson correlation coefficient, the similarity of the background scattering peak can be obtained.

[0061] In the method for rapid screening of cosmetic consistency based on X-ray fluorescence spectroscopy of the present invention, the XRF comprehensive similarity analysis in step (3) comprises the following steps:

[0062] The similarity between the main element XRF fingerprint and the scattered background XRF fingerprint was analyzed, and the two similar

[0063] Different weights are assigned to the results.

[0064] Weight parameter table

[0065] index Full element XRF fingerprint Scattering background XRF fingerprint Specific indicators f1 f2 Correlation coefficient weight 0.8 0.2

[0066] Combined analysis and comprehensive similarity calculation:

[0067] S=∑si·fi

[0068] S: comprehensive similarity;

[0069] si: similarity between all-element characteristic spectra and scattering background spectra;

[0070] fi: spectral similarity contribution weight.

[0071] In the method for rapid screening of cosmetic consistency based on X-ray fluorescence spectroscopy of the present invention, the consistency analysis in step (4) comprises the following steps:

[0072] Analysis and Evaluation Form

[0073] Similarity 0≤S≤0.5 0.5<S≤0.7 0.7<S≤0.8 0.8<S≤1.0 Product consistency Very poor consistency Average consistency High consistency High consistency

[0074] The established cosmetics XRF consistency analysis method is used to compare the similarity of actual cosmetics samples, and the consistency analysis results are finally evaluated according to the analysis evaluation table.

[0075] The method for rapid screening of cosmetic consistency based on X-ray fluorescence spectroscopy of the present invention differs from the prior art in that:

[0076] The method presented in this paper is a rapid identification method based on X-ray fluorescence spectrometry and the formulation and component characteristics of cosmetics. This method is efficient and rapid, requires no special site requirements, and can rapidly verify the quality of cosmetics within 15 minutes, thereby ensuring efficient and high-quality warehousing of merchants' products. This method provides accurate and rapid identification results, is time-efficient, and low-cost, making it particularly suitable for rapid identification scenarios required by on-site regulatory authorities at ports and markets.

[0077] The method for rapid screening of cosmetic consistency based on X-ray fluorescence spectroscopy according to the present invention will be further described below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1 This is the high-energy spectrum of the standard product in Example 2 of the present invention;

[0079] Figure 2The low-energy spectrum of the standard product in Example 2 of the present invention;

[0080] Figure 3 The mid-energy spectrum of the standard product in Example 2 of the present invention;

[0081] Figure 4 The low-energy spectrum of the sample in Example 2 of the present invention;

[0082] Figure 5 The mid-energy spectrum of the sample in Example 2 of the present invention;

[0083] Figure 6 This is the high-energy band spectrum of the sample in Example 2 of the present invention. DETAILED DESCRIPTION

[0084] Example 1

[0085] A method for rapid screening of cosmetic consistency based on X-ray fluorescence spectroscopy comprises the following steps:

[0086] (1) Sampling and loading, setting instrument parameters, irradiating the sample with X-rays, and obtaining the XRF fingerprint spectrum;

[0087] The sampling and loading process includes: fixing the test film to the bottom of the XRF sample cup and clamping it with the sample cup hoop;

[0088] When the cosmetic is a solid sample, a layer of the cosmetic sample is evenly applied on the test film inside the sample cup to completely cover the test film;

[0089] When the cosmetics are aqueous solutions and emulsions, directly put in a layer of cosmetic sample to completely cover the sample injection film and set aside.

[0090] The sample is irradiated with X-rays, and the inner shell electrons of the element atoms are excited to produce electron transitions that emit characteristic X-rays. The energy setting is related to the power of the photomultiplier tube, with a maximum power of 12W, a maximum excitation voltage of 70KV, and a maximum sample diameter of 48mm. Based on the characteristics of the cosmetics, the optimal instrument testing conditions are as follows:

[0091] Test conditions Voltage / KeV Current / uA Power / W Sampling time / s Detector dead time Low-Energy 15 350 5.25 6.44 30％ Mid-Energy 30 100 11 139.18 30％ Hig-Energy 70 180 12 74.26 30％

[0092] (2) Establish a database of XRF fingerprints of cosmetic standard samples;

[0093] According to the XRF fingerprint determination method studied in step (1), a cosmetics standard sample XRF fingerprint database is established;

[0094] Select no less than 10 batches of the same cosmetic samples and perform XRF analysis in different energy bands to obtain energy spectra and the content of each characteristic element;

[0095] The original XRF spectrum was Gaussian filtered, and the characteristic peak of the element with the highest count rate and the best goodness of fit in the FP algorithm was selected as the reference peak (base peak). The XRF software also obtained the characteristic peak count rates of other elements;

[0096] Selection and determination of fingerprint spectrum quantitative information parameters: a. Count rate of characteristic peak; b. Ratio of count rate of characteristic peak to count rate of reference peak; c. Shape and intensity decomposition of scattering peak.

[0097] (3) Similarity analysis of XRF fingerprints of the sample to be tested and the standard,

[0098] The fingerprint obtained in the invention is combined with the chemical pattern recognition method in chemometrics to perform product consistency identification (similarity analysis). XRF fingerprint similarity analysis mainly considers two aspects: one is the similarity analysis of the full element spectrum in the sample (including the number, position and order of fingerprint peaks, and whether the approximate content ratios between each common element are similar), and the other is the similarity analysis of the background scattering spectrum (quantitative comparison of total peak area). The fingerprint obtained by XRF spectroscopy assigns different weights to the similarity of the full element spectrum and the similarity of the scattering background spectrum to obtain the comprehensive similarity result of the XRF fingerprint spectrum.

[0099] The specific steps include:

[0100] I. Full element XRF spectrum similarity analysis:

[0101] Fingerprint similarity algorithm: The ratios of the count rates of each characteristic peak in an energy band of the XRF fingerprint to the reference peak r1, r2, r3, ..., rn form an n-dimensional space vector R1 = r1, r2, r3, ..., rn. Each sample contains three spectra of low energy, medium energy, and high energy, namely three space vectors R1, R2, and R3. The Pearson correlation coefficients of the corresponding energy band space vectors of the two samples are calculated respectively, and the three correlation coefficients are weighted according to the number of characteristic peaks in each energy band. The total correlation coefficient of the characteristic peaks is obtained by linear addition. The Pearson correlation coefficient is a centralized correlation calculation method, and its calculation formula is as follows:

[0102]

[0103] S: Pearson correlation coefficient;

[0104] Xi: the spatial vector R of the sample to be investigated;

[0105] Yi: space vector of the control spectrum;

[0106] The weighted calculation method for the total correlation coefficient of characteristic peaks is as follows:

[0107]

[0108] in, And C i is the number of characteristic peaks in this energy band.

[0109] II. Background scattering spectrum similarity analysis:

[0110] The scattering peak is filtered by Savitzky-Golay, and the fitting formula is:

[0111]

[0112] Among them, a k Construct a polynomial for fitting the scattering peak, where n = -m, ...0, ...m, which is 2m+1 integers;

[0113] The fitted residuals are:

[0114]

[0115] Where x[i] is the vector representing the scattering peak to be input;

[0116] The filtering result is expressed as:

[0117] y[0]=p(0)=a0

[0118] To minimize ε, its partial derivatives with respect to each parameter should be 0, that is:

[0119]

[0120] Substitute and simplify to get:

[0121]

[0122] Introduce the matrix A={a ni}, construct matrix B = A T A, then:

[0123] Ba=A T Aa=A T X,

[0124] a=(A T A) -1 A T X=HX

[0125] Align the filtered scattering peaks of the control sample and the test sample according to the number of channels, and then perform principal component analysis on each scattering peak spectrum;

[0126] First, the original data is standardized to obtain the standardized matrix Z:

[0127]

[0128] i=1,2,…,p

[0129] j=1,2,…,n

[0130] where x ij represents n samples of p-dimensional vectors,

[0131] The correlation coefficient matrix R of the spectrum X is expressed as follows:

[0132]

[0133] in

[0134] According to the characteristic equation of R|R-λI P |=0 to obtain p characteristic roots, according to To determine the number of principal components m,

[0135] The principal component vector retains more than 95% of the information of the original spectrum.

[0136] Solve the system of equations R b =λ j b gets the unit eigenvector The principal component vector is then expressed as:

[0137]

[0138] Among them U i That is the i-th principal component;

[0139] Will U ij By calculating the Pearson correlation coefficient, the similarity of the background scattering peak can be obtained.

[0140] III.XRF comprehensive similarity analysis:

[0141] The similarity between the main element XRF fingerprint and the scattered background XRF fingerprint was analyzed, and the two similar

[0142] The similarity results are assigned different weights and combined for analysis and calculation:

[0143] S=∑si·fi

[0144] S: comprehensive similarity;

[0145] si: similarity between all-element characteristic spectra and scattering background spectra;

[0146] fi: spectral similarity contribution weight.

[0147] Weight parameter table

[0148] index Full element XRF fingerprint Scattering background XRF fingerprint Specific indicators f1 f2 Correlation coefficient weight 0.8 0.2

[0149] (4) XRF consistency analysis of the sample to be tested and the standard:

[0150] The established cosmetics XRF consistency analysis method was used to compare the similarity of actual cosmetics samples, and the consistency analysis results were finally evaluated based on the analysis evaluation table.

[0151] Analysis and Evaluation Form

[0152] Similarity 0≤S≤0.5 0.5<S≤0.7 0.7<S≤0.8 0.8<S≤1.0 Product consistency Very poor consistency Average consistency High consistency High consistency

[0153] Example 2

[0154] Makeup 1 and Makeup 2 (same air cushion cream from different channels), where air cushion cream 1 was obtained from a regular brand manufacturer channel (as a standard sample), and air cushion cream 2 was purchased from the market (as a sample to be identified). The fingerprints of air cushion cream 1 and air cushion cream 2 were obtained after testing, and the similarity of the full element fingerprint spectrum and the scattering background fingerprint spectrum were obtained based on the fingerprint spectrum indicators. Fingerprint spectrum see Figures 1 to 6 The similarity of the full element fingerprint spectrum considers the three bands of low energy, medium energy and high energy, and calculates the Pearson correlation coefficient according to the formula to obtain the corresponding similarity value; the similarity of the scattering background fingerprint spectrum aligns the scattering peaks of the control sample and the test sample after filtering according to the number of channels (energy), and then performs principal component analysis on each scattering peak spectrum according to the corresponding formula, and finally calculates the Pearson correlation coefficient according to the formula to obtain the similarity value. The fingerprint spectra of the sample and the standard at high energy, medium energy and low energy bands are shown in Figures 1 to 6 (The spectrum contains element spectrum peaks and scattering background peaks).

[0155] Finally, the XRF fingerprint comprehensive similarity value S is calculated according to the different weight values ​​of different fingerprint indexes:

[0156] S=ΣF i ·S i =0.8×0.6+0.2×0.5=0.58

[0157] Conclusion: According to the consistency analysis evaluation table, the consistency evaluation results of Air Cushion Cream 1 and Air Cushion Cream 2 were "general consistency".

[0158] The embodiments described above are merely descriptions of preferred implementations of the present invention and are not intended to limit the scope of the present invention. Without departing from the spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should fall within the scope of protection determined by the claims of the present invention.

Claims

1. A method for rapid screening of cosmetic consistency based on X-ray fluorescence spectroscopy, characterized by: The steps include: (1) Sampling and loading, setting instrument parameters, irradiating the sample with X-rays, and obtaining the XRF fingerprint spectrum; (2) Establishing a database of XRF fingerprints of cosmetic standard samples: Establishing a database of XRF fingerprints of cosmetic standard samples according to step (1); Select no less than 10 batches of the same cosmetic samples and perform XRF analysis in different energy bands to obtain energy spectra and the content of each characteristic element; The original XRF spectrum was Gaussian filtered, and the characteristic peak of the element with the highest count rate and the best goodness of fit in the FP algorithm was selected as the reference peak. The XRF software also obtained the characteristic peak count rates of other elements. Selection and determination of fingerprint spectrum quantitative information parameters: a. Count rate of characteristic peak; b. Ratio of the count rate of characteristic peak to the count rate of reference peak; c. Shape and intensity decomposition of scattering peaks; (3) Similarity analysis of the XRF fingerprints of the sample to be tested and the standard, including full-element XRF spectrum similarity analysis, background scattering spectrum similarity analysis and XRF comprehensive similarity analysis; The XRF comprehensive similarity analysis includes the following steps: By analyzing the similarity between the full-element XRF spectrum and the background scattering spectrum, and assigning different weights to the two similarity results: The similarity contribution weight f1 of all-element XRF spectrum is 0.8; the similarity contribution weight f2 of background scattering spectrum is 0.2; Combined analysis and comprehensive similarity calculation: ， S: comprehensive similarity; si: similarity between all-element XRF spectrum and background scattering spectrum; fi: similarity contribution weight of all-element XRF spectrum and background scattering spectrum; (4) XRF consistency analysis of the test sample and the standard: Use the established cosmetics XRF consistency analysis method to conduct a comprehensive similarity comparison of the actual cosmetics samples, and obtain the consistency analysis results based on the final evaluation of the analysis evaluation table; The analysis and evaluation criteria are: When 0≤ S ≤0.5, the product consistency is very poor; when 0.5≤ S ≤0.7, the product consistency is average; when 0.7≤ S ≤0.8, the product consistency is relatively high; when 0.8≤ S ≤1.0, the product consistency is high.

2. The method for rapid screening of cosmetic consistency based on X-ray fluorescence spectroscopy according to claim 1, characterized in that: The sampling and loading process in step (1) includes: fixing the test film to the bottom of the XRF sample cup and clamping it with a sample cup hoop; When the cosmetic is a solid sample, a layer of the cosmetic sample is evenly applied on the test film inside the sample cup to completely cover the test film; When the cosmetics are aqueous solutions and emulsions, directly put a layer of cosmetic sample into the film to completely cover the sample membrane and set aside.

3. The method for rapid screening of cosmetic consistency based on X-ray fluorescence spectroscopy according to claim 2, characterized in that: The instrument parameters in step (1) are set as follows: The test conditions were low energy, with a voltage of 15 KeV, a current of 350 uA, a power of 5.25 W, a sampling time of 6.44 s, and a detector dead time of 30%. The test conditions are medium energy, voltage is 30 KeV, current is 100 uA, power is 11 W, sampling time is 139.18 s, and detector dead time is 30%; When the test conditions are high energy, the voltage is 70 KeV, the current is 180 uA, the power is 12 W, the sampling time is 74.26 s, and the detector dead time is 30%.

4. The method for rapid screening of cosmetic consistency based on X-ray fluorescence spectroscopy according to claim 3, characterized in that: The full element XRF spectrum similarity analysis in step (3) includes the following steps: Fingerprint similarity algorithm: The ratios of the count rates of each characteristic peak in an energy band of the XRF fingerprint to the reference peak r1, r2, r3, …, rn form an n-dimensional space vector R1=r1, r2, r3, …, rn. Each sample contains three spectra of low energy, medium energy, and high energy, i.e., three space vectors R1, R2, and R3. The Pearson correlation coefficients of the corresponding energy band space vectors of the two samples are calculated respectively. The three correlation coefficients are weighted according to the number of characteristic peaks in each energy band, and the total correlation coefficient of the characteristic peaks is obtained by linear addition. The weighted calculation method for the total correlation coefficient of characteristic peaks is as follows: ,in, ,and C i is the number of characteristic peaks in this energy band.

5. The method for rapid screening of cosmetic consistency based on X-ray fluorescence spectroscopy according to claim 4, characterized in that: The background scattering spectrum similarity analysis in step (3) includes the following steps: The scattering peak is filtered by Savitzky-Golay, and the fitting formula is: ， in, Construct a polynomial to fit the scattering peak, , is 2m+1 integers; The fitted residuals are: , where x\left [ {n} \right ] is the vector representing the scattering peak to be input; The filtering result is expressed as: , To make To minimize the error, its partial derivatives with respect to each parameter should be 0, that is: , Substitute and simplify to get: , Introducing the Matrix , construct the matrix ,but: , Align the filtered scattering peaks of the control sample and the test sample according to the number of channels, and then perform principal component analysis on each scattering peak spectrum; First, the original data is standardized to obtain the standardized matrix Z : , , , in represents n samples of p-dimensional vectors, ; The correlation coefficient matrix R of the scattering peak spectrum is expressed as follows: ; in ; According to the characteristic equation of R Obtain p characteristic roots, according to , determine the number of principal components m, so that the principal component vector retains more than 95% of the information of the original spectrum; Solving a system of equations The unit eigenvector , so the principal component vector is expressed as: , in That is the i principal components; Will By calculating the Pearson correlation coefficient, the similarity of the background scattering peak can be obtained.

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