Matrix correction method for apatite sulfur isotope microanalysis based on sims

Abstract

The application provides a SIMS-based apatite sulfur isotope micro-area analysis matrix correction method, and belongs to the field of apatite sulfur isotope calibration and SIMS micro-area analysis. The method collects at least three different apatite micro-area in-situ sulfur isotope analysis standards; prepares sample targets of the analysis standards and the to-be-measured unknown sample; selects at least two analysis standards as monitoring standards; tests the sulfur isotope signals of the sample by using a SIMS method; obtains a time drift slope according to the monitoring standard data points, and corrects the data points of the analysis standards and the unknown sample for time drift to obtain 34 S / 32 S, delta 34 S and the leveling value of IMF; constructs an instrument fractionation relationship formula and an intercept relationship formula of the analysis standards, solves the first slope, the second slope and the second intercept, and constructs a recommended value calculation formula after matrix effect correction to obtain the delta 34 S value of the unknown sample. The application improves the accuracy and precision of apatite sulfur isotope micro-area analysis.

Description

Technical Field

[0001] This invention belongs to the field of apatite sulfur isotope calibration and SIMS micro-area analysis, specifically relating to a matrix correction method for apatite sulfur isotope micro-area analysis based on SIMS. Background Technology

[0002] Apatite [Ca5(PO4)3(F,Cl,OH)] is a widely distributed phosphate mineral in nature, prevalent in the diagenetic and mineralization stages of various types of mineral deposits. Due to its high physicochemical stability and ability to accommodate rare earth elements (REEs), Sr, Y, Th, U, F, Cl, S, and other trace elements and volatile components, its mineralogical composition can effectively record the physicochemical conditions of magma crystallization, hydrothermal activity, fluid-rock reactions, and mineralization processes. Therefore, apatite has become an important indicator mineral for studying the evolution of magma-hydrothermal systems, the source of ore-forming materials, and the formation mechanism of mineral deposits.

[0003] Among the many trace elements that can be captured by apatite, sulfur has attracted attention due to its unique geochemical behavior. Sulfur is a key volatile component of the Earth system, widely present in the atmosphere, hydrosphere, biosphere, lithosphere, and various internal spheres of the Earth, mainly in the form of H2S and SO2 gases, sulfide minerals, sulfate minerals, elemental sulfur, and sulfur-containing organic compounds. The mass fraction of sulfur in apatite can reach up to 2.9%, and its content varies in various mineral deposits or rock masses. It is widely used in the study of different types of mineral deposits, such as tracing and constraining key issues such as magma oxygen fugacity and the changing trends of sulfur content during reactive magma evolution. Furthermore, the sulfur isotopic composition in apatite can be used to record the source, migration, and isotopic fractionation processes of sulfur in magma-hydrothermal systems, and is an important indicator for constraining magma degassing, magma mixing, crystallization evolution, the addition of exogenous sulfur, and the evolution of ore-forming fluids.

[0004] Currently, conventional methods for sulfur isotope analysis include comprehensive analysis using stable isotope ratio mass spectrometry, multi-collector inductively coupled plasma mass spectrometry, or thermal ionization mass spectrometry. These methods typically yield high-precision sulfur isotope analysis results (for δ¹²⁺ ¹³ ... 34 While apatite (S, 2SD < 0.2‰) can be analyzed, it requires a complex chemical pretreatment process and a large sample volume. However, apatite generally possesses a complex internal structure and often coexists closely with various minerals. For example, apatite in granitic rocks often exhibits oscillatory zoning or core-rim structures. These fine compositional partitions can record changes in magma crystallization conditions, magma mixing, multiple magma superpositions, and local magma composition variations caused by crystallization differentiation. Traditional holistic analysis methods can only obtain the average sulfur isotope composition of the sample, making it difficult to identify the microscale isotopic differences preserved in different structural domains within individual apatite grains. Therefore, they cannot effectively capture detailed information about diagenetic and mineralization processes.

[0005] In recent years, with the advancement of micro-area in-situ analysis techniques, methods such as secondary ion mass spectrometry (SIMS) have been increasingly applied to sulfur isotope analysis in apatite. Compared with traditional whole-area analysis, micro-area in-situ analysis does not require complete sample destruction and can perform point-to-point analysis on specific structural domains within mineral grains, thereby obtaining sulfur isotope information corresponding to mineral structure, compositional zoning, and coexisting mineral relationships. Among these, SIMS has advantages such as low sample loss, low background signal, high spatial resolution, and the ability to simultaneously acquire multi-sulfur isotope information. It is suitable for apatite samples with complex internal structures, fine zoning, or complex mineral intergrowth relationships, and has significant application potential in high spatial resolution in-situ analysis of apatite sulfur isotopes.

[0006] Early studies suggested that differences in F, Cl, and OH composition in apatite did not cause significant SIMS sulfur isotope matrix effects, and that different crystallographic orientations had little impact on apatite sulfur isotope analysis results. However, subsequent studies, through reprocessing existing data, revealed a negative correlation between instrumental mass fractionation (IMF) and apatite sulfur concentration, indicating that apatite SIMS sulfur isotope analysis may still be affected by sulfur content-related matrix effects. Therefore, matrix effects remain a key focus and challenge in in-situ sulfur isotope analysis of apatite SIMS micro-regions.

[0007] In existing techniques, SIMS isotope analysis requires the use of standard materials whose mineralogical characteristics and chemical composition match those of the target sample to correct for variations in secondary ion signal intensity and IMF caused by matrix differences. Currently, a series of standard materials suitable for apatite sulfur isotope analysis have been reported, with SO3 contents ranging from approximately 0.21% to 1.71%, and corresponding recommended δ¹⁸ ppm values ​​have been provided. 34 The S-value. Based on standard materials, the conventional calibration method for SIMS sulfur isotope analysis is the single standard bracket (SSB) calibration method. Its basic principle is: before and after every 4–10 sample analyses, a matrix-matched standard with a known sulfur isotope composition is repeatedly measured, assuming the standard's δ0.05 value is the correct value. 34 The difference between the recommended value and the measured value of S is the instrument mass fraction of this batch of experiments. Then, assuming that the unknown sample and the standard sample have the same IMF, the δ of the unknown sample is obtained. 34 S value. However, due to significant differences in sulfur content and F-Cl-OH composition among different apatite samples, coupled with the low secondary ion signal during trace element sulfur analysis using small-spot SIMS and the complex apatite matrix effect, the single standard used in the SSB correction method cannot completely match all unknown samples, resulting in a corrected δ value.34 The S value has a significant deviation, making it impossible to accurately identify the S isotopes in apatite. Summary of the Invention

[0008] In view of the above-mentioned defects or deficiencies in the prior art, the present invention aims to provide a matrix correction method for apatite sulfur isotope micro-area analysis based on SIMS. The method uses a combination of multiple apatite standards to jointly correct the matrix effect in apatite SIMS sulfur isotope analysis, thereby reducing the data bias caused by the matrix effect and improving the data precision and accuracy of apatite sulfur isotope micro-area analysis.

[0009] To achieve the above objectives, the embodiments of the present invention adopt the following technical solutions:

[0010] A matrix correction method for apatite sulfur isotope micro-area analysis based on SIMS, the method comprising the following steps:

[0011] Step S1: Collect at least three different in-situ sulfur isotope analysis standards for apatite micro-regions; prepare a sample target, wherein the sample target includes the analysis standards and the unknown sample to be tested;

[0012] Step S2: Select at least two analytical standards as monitoring standards simultaneously; use the SIMS method to test the sulfur isotope signals of the analytical standards, unknown sample, and monitoring standards on the sample target; the sulfur isotope signals include... 34 The count rate of S and 32 The count rate of S;

[0013] Step S3: Using a linear regression model with grouping variables, all data points of the monitoring standard are jointly fitted, and the time drift slope is obtained by solving the fitted model.

[0014] Step S4: Using the time drift slope, perform time drift correction on all data points of all analytical standards and unknown samples to obtain... 34 S / 32 S-leveling value; and based on 34 S / 32 S-leveling value, calculate δ for each analytical standard and unknown sample. 34 S-leveling value and instrument mass fractionation IMF leveling value;

[0015] Step S5, to analyze the standard sample 34 S / 32 The S-leveling value is the independent variable, and the IMF-leveling value is the dependent variable. An instrument fractionation relationship is constructed for each analytical standard, and the first slope and first intercept are obtained by solving. The first slope is the same for all leveling relationships, but the first intercept differs for different analytical standards. Then, using the analytical standard... 34 S / 32With S-leveling as the independent variable and the first intercept as the dependent variable, the intercept relationship of all analytical standards is constructed, and the second slope and the second intercept are obtained by solving.

[0016] Step S6: Based on the first slope, the second slope, and the second intercept, construct a formula for calculating the recommended value after matrix effect correction; substitute the test data of the unknown sample into the formula for calculating the recommended value to obtain the δ of the unknown sample. 34 S-value.

[0017] In a preferred embodiment of the present invention, the preparation of the sample target includes:

[0018] Step S11: Prepare glass slides of the predetermined size and apply double-sided tape; arrange each standard sample in a row according to the order of particle size from largest to smallest, and stick them in a circle with a diameter of about 1 cm on the double-sided tape; arrange the analytical standard samples and unknown samples in order from top to bottom;

[0019] Step S12: Place the smooth polyethylene hollow column vertically on the double-sided adhesive, ensuring that the circular part of the sample is centered in the polyethylene hollow column; slowly inject the mixture of epoxy resin and coagulant after vacuuming along the inner surface of the polyethylene hollow column, vacuum again and let it stand to allow the mixture to solidify, obtaining a solidified sample sheet that can be removed from the polyethylene hollow column; use fine sandpaper and a polishing pad to polish the sample sheet in sequence, so that both the analytical standard and the unknown sample to be tested are exposed on one side of the sample sheet.

[0020] Step S13: Clean the sample slices;

[0021] Step S14: Deposit conductive material to obtain sample target.

[0022] In a preferred embodiment of the present invention, the testing process of step S2 using the SIMS method is as follows:

[0023] Let the number of analytical standard samples be Q1, the number of unknown samples be Q2, and the number of monitoring standard samples be Q3; and 2≤Q3≤Q1;

[0024] After setting the test parameters, the Q1 analytical standards are tested sequentially in a forward order, with each standard tested at P1 consecutive points. Next, the Q2 unknown samples are tested, with each monitoring standard sample's test point inserted at intervals of P2 unknown sample test points within the unknown sample test sequence. At the end of the unknown sample testing, each analytical standard sample is tested again in a reverse order, with P1 consecutive points tested. This process is repeated for all analytical standards, unknown samples, and monitoring standards, yielding all analytical points for all samples. 34 S and 32 The count rate of S.

[0025] In a preferred embodiment of the present invention, when two monitoring standard samples are used in step S3, the fitting model for the joint fitting is as follows:

[0026] (1)

[0027] In equation (1), For the first The first monitoring standard sample test points 34 S / 32 S ratio; The indicator variable is the monitoring standard, with a value of 0 for the first monitoring standard and a value of 1 for the second monitoring standard; β0 is the initial intercept of the first monitoring standard, and β1 is the intercept offset of the second monitoring standard relative to the first monitoring standard. The time drift slope shared by the two standards. This is the residual term.

[0028] As a preferred embodiment of the present invention, based on the time drift slope Time drift correction is applied to each data point using the following formula:

[0029] (2)

[0030] In equation (2), The serial number of the test point; Indicates the first test points 34 S / 32 S ratio, Indicates the first After time drift correction at each test point 34 S / 32 S-leveling value.

[0031] As a preferred embodiment of the present invention, the δ 34 The formula for calculating the S-leveling value is as follows:

[0032] (3)

[0033] In equation (3), Indicates the first δ at each test point 34 S-leveling value; International standard for representing sulfur isotope ratios.

[0034] As a preferred embodiment of the present invention, the formula for calculating the IMF leveling value is as follows:

[0035] Based on each analytical standard and each test point 34 S / 32 S-leveling value and analytical standard 34 S / 32 The S-recommended value is used to calculate the IMF balancing value, using the following formula:

[0036] = (4)

[0037] In equation (4), This represents the test point sequence number corresponding to the r-th analytical standard sample in the test point sequence {1,2,…,j,…,M}. This represents the r-th analytical standard. 34 S / 32 S recommended value.

[0038] In a preferred embodiment of the present invention, the instrument fractionation relationship for each analytical standard sample in step S5 is as follows:

[0039] = (5)

[0040] In equation (5), k1 is the first slope shared by all standards, reflecting the common law of matrix effect on IMF; b1 is the first intercept unique to each standard, representing the degree to which each standard deviates from the common law due to compositional differences.

[0041] The intercept relationship is as follows:

[0042] (6)

[0043] In equation (6), k2 is the second slope and b2 is the second intercept.

[0044] In a preferred embodiment of the present invention, the IMF leveling value for each unknown sample is calculated using the following formula:

[0045] = (7)

[0046] The formula for calculating the recommended value for an unknown sample is as follows:

[0047] (8)

[0048] In equation (8), This represents the test point sequence number corresponding to the s-th unknown sample in the test point sequence {1,2,…,j,…,M}.

[0049] As a preferred embodiment of the present invention, the formula for calculating the recommended value after matrix effect correction is as follows:

[0050] (9)

[0051] In equation (9), This represents the test point sequence number corresponding to the s-th unknown sample in the test point sequence {1,2,…,j,…,M}; For the s-th unknown sample, based on time-balanced... 34 S / 32 S ratio, δ after leveling the s-th unknown sample 34 S value, k1, k2 and b2 are the first slope, second slope and second intercept obtained by solving, respectively.

[0052] The technical solutions provided in the embodiments of the present invention have the following beneficial effects:

[0053] First, this invention achieves high spatial resolution with a 10μm beam spot, using apatite δ 34 The analytical precision of sulfur isotopes (S) remains better than 0.8‰ (2SD), approaching or exceeding the analytical level achieved by previous researchers using a 15μm beam spot. This allows the present invention to identify finer sulfur isotope variations, making it suitable for apatite samples with small particles or complex zonal structures, thus overcoming the technical constraints between high resolution and high precision. Secondly, by using a combination of standards with low, medium, and high sulfur isotope endmembers to correct for time drift and matrix effects, optimal correction results are ensured for apatite samples with different sulfur content ranges, demonstrating strong flexibility and wide applicability. Furthermore, the correction method in this invention has been successfully applied to multiple sets of published SIMS raw data from different laboratories, instrument models, and analytical batches, with corrected δ¹⁸ saturations of each standard sample. 34 The deviations of the S value from the recommended value are both less than 0.7‰, indicating that the present invention has good universality and scalability.

[0054] Of course, implementing any product or method of the present invention does not necessarily require achieving all of the advantages described above at the same time. Attached Figure Description

[0055] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0056] Figure 1 This is a flowchart of the matrix correction method for apatite sulfur isotope micro-area analysis based on SIMS as described in the embodiments of the present invention;

[0057] Figure 2 This is a schematic diagram of the sample target in an embodiment of the present invention;

[0058] Figure 3 This is an example of an apatite standard sample from an embodiment of the present invention. 34 S / 32 Trend graph of S ratio as a function of analysis sequence number;

[0059] Figure 4 This is the apatite analysis standard after time drift correction in the embodiments of the present invention. 34 S / 32 Trend graph of S ratio as a function of analysis sequence number;

[0060] Figure 5 The IMF leveled value of the apatite analytical standard in this embodiment of the invention is... 34 S / 32 Correlation of S-leveling values. Detailed Implementation

[0061] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. It should be noted that, without conflict, the embodiments and features in the embodiments of the present invention can also be combined with each other.

[0062] It should be noted that similar reference numerals and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. In the description of the embodiments of the present invention, the terms "first," "second," "third," "fourth," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance. In addition, sometimes a subscript such as W1 may be written in a non-subscript form such as W1, and their meanings are consistent unless the distinction is emphasized.

[0063] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0064] To address the matrix effect issue in the analysis of sulfur in apatite using the SIMS method, this invention provides a SIMS-based matrix correction method for micro-area analysis of sulfur isotopes in apatite. This method establishes a time-balanced matrix correction model through a combination of multiple standard samples. 34 S / 32 The functional relationship between the S ratio and IMF, thereby correcting for matrix effects, enables the determination of the δ-value of unknown samples. 34 High-precision measurement of S-value.

[0065] like Figure 1 As shown, the SIMS-based matrix correction method for apatite sulfur isotope micro-area analysis includes the following steps:

[0066] Step S1: Collect at least three different in-situ sulfur isotope analysis standards for apatite micro-regions; prepare a sample target, wherein the sample target includes the analysis standards and the unknown sample to be tested.

[0067] In this step, three standards with significantly different sulfur isotope compositions are used as the analytical standards: a high-sulfur isotope value standard, a low-sulfur isotope value standard, and an intermediate-value standard. The analytical standards are selected from SAP-1, Durango-A, Durango-B, MG, OL-1, Sly-1, Big1, and / or Mdg-1. Specifically, the high-sulfur isotope value standard can be Sly-1, the low-sulfur isotope value standard can be Durango-A and / or Durango-B, and the intermediate-value standard can be SAP1, OL-1, and / or Big1.

[0068] In one executable embodiment, each analytical standard and unknown sample comprises at least 10 particles with a particle size of 100-150 μm.

[0069] The process for preparing the sample target is as follows:

[0070] Step S11: Prepare a 10cm*10cm glass slide and apply 10cm*5cm double-sided tape. Arrange each sample in a row according to particle size from largest to smallest, and stick them in a circle with a diameter of about 1cm on the double-sided tape. Arrange the analytical standard and unknown samples from top to bottom. If there are a total of 8 samples including the analytical standard and unknown samples, arrange them in 8 rows.

[0071] Step S12, as follows Figure 2 As shown, a smooth polyethylene hollow column (approximately 25.40 mm in diameter) is placed vertically on the double-sided adhesive tape, ensuring that the 1 cm diameter circle for attaching the sample is centered within the polyethylene hollow column. A mixture of epoxy resin and coagulant, after vacuuming, is slowly injected along the inner surface of the polyethylene hollow column. Vacuuming is repeated, and the mixture is allowed to solidify, resulting in a solidified sample sheet that can be removed from the polyethylene hollow column. The sample sheet is then polished using fine sandpaper and a polishing pad, ensuring that both the analytical standard and the unknown sample to be tested are exposed on one side of the sample sheet.

[0072] Step S13, cleaning the sample slices: First, clean the sample surface with water; second, place the sample in a beaker containing alcohol and use an ultrasonic cleaner to ultrasonically clean the sample for three minutes; third, place the sample in a drying oven to dry for one hour.

[0073] Step S14: Deposit conductive material to obtain the sample target. Using a Quorum Q150TE gold plating instrument, a continuous gold film is deposited on the exposed side of the cleaned circular sample. To ensure good conductivity of the sample, the plating thickness is 20nm~50nm.

[0074] Step S2: Select at least two analytical standards as monitoring standards simultaneously; use the SIMS method to test the sulfur isotope signals of the analytical standards, unknown sample, and monitoring standards on the sample target; the sulfur isotope signals include... 34 The count rate of S and 32 The count rate of S.

[0075] In this step, let the number of analytical standards be Q1, the number of unknown samples be Q2, and the number of monitoring standards be Q3; and 2≤Q3≤Q1. The testing process using the SIMS method is as follows: After setting the test parameters, first, test Q1 analytical standards in the order of standard one, standard two, and standard three, continuously testing each analytical standard for P1 points to ensure stable test conditions and instrument status; then, test Q2 unknown samples. To ensure test accuracy, at least two analytical standards are selected as monitoring standards. In the test sequence of unknown samples, test one point of each monitoring standard is inserted at intervals of P2 unknown sample test points to correct for offset and monitor the external reproducibility of the analysis. Mutual verification and correction between different standards can be used to eliminate instrument mass fractionation; when the unknown sample test is completed, test each analytical standard again in the order of standard three, standard two, and standard one, continuously testing P1 points to complete the testing of all analytical standards, unknown samples, and monitoring standards, obtaining all analytical points of all samples. 34 S and 32 S-test value, i.e. 34 S and 32 The count rate of S. The value of P1 ranges from 5 to 8; the value of P2 ranges from 3 to 5. During actual testing, all test points are numbered sequentially according to the testing order, resulting in a test point sequence {1,2,…,j,…,M}, where M represents the number of test points. The test point sequence {1,2,…,j,…,M} includes three types of sequence numbers depending on the sample: the test point sequence number for the monitoring standard sample. Analytical standard test point sequence number Test point serial number of unknown sample Each serial number has a fixed corresponding value, such as, , .

[0076] When performing SIMS testing in this step, preferably, Cs is used. + As the primary ion beam, the accelerating voltage is 10 kV, the beam current is approximately 0.7 nA, and the primary ion beam is focused to a diameter of approximately 10 μm. During analysis, a 5 × 5 μm grating scan is performed on the sample surface. A diffuse electron gun is used for charge compensation during analysis, employing a Gaussian illumination primary ion beam mode to focus on the sample and excite secondary ions. Secondary sulfide ions are extracted through a 10 kV high voltage, focused at the center of the 5000 μm field stop of a 61 μm entrance slit, and energy filtered using a 60 eV bandwidth. The mass spectrometer operates at a mass resolution of approximately 4500, sufficient to resolve potential interfering peaks (such as...). 31 P 1 H to 32 (Interference from S). Isotopes were measured using multiple receiver modes. 32 S is received by the Faraday Cup. 34 Because the signal from S is relatively weak, it is received by a more sensitive electron multiplier. Each analytical point first undergoes a 100-second pre-etching process to remove the surface coating of the micro-area and reduce contamination from the target preparation process. Subsequently, a secondary ion beam autofocusing is performed through the field aperture to reduce analytical errors caused by variations in sample surface morphology. The energy and mass peaks are scanned sequentially to eliminate analytical errors caused by sample charge accumulation and to correct for magnetic field drift over time. During the formal acquisition process, each analytical point consists of 50 cycles, with a single integration time of 4 seconds. Under these conditions, 32 The typical count rate of S is approximately 10. 6 cps.

[0077] Step S3: Using a linear regression model with grouping variables, all data points of the monitoring standard are jointly fitted, and the time drift slope is obtained by solving the fitted model.

[0078] In this step, data from at least two monitoring standards during the test are used to correct the time drift of the remaining standards.

[0079] During the test, due to the slow changes in the state of the electron gun ion coil, the intensity of the primary ion beam may drift, thus affecting the measured intensity. 34 S / 32 The S ratio changes systematically over time. For example... Figure 3 As shown, the analytical standard sample 34 S / 32 The S-ratio exhibits a linear decreasing trend with the analysis sequence number (i.e., time). To eliminate the influence of time drift on the isotope ratio measurement, two apatite standards were used as monitoring standards, and their measurements were interspersed throughout the analysis of the other five standards. 34 S / 32 The S-ratio exhibits similar slopes but different intercepts as the analysis sequence number changes. Therefore, a linear regression model with grouping variables is used to jointly fit all data points from the two monitoring standards to eliminate the effect of time drift.

[0080] When two monitoring standards are used, the fitting model for the joint fitting is as follows:

[0081] (1)

[0082] In equation (1), For the first The first monitoring standard sample test points 34 S / 32 S ratio; The indicator variable is the monitoring standard, with a value of 0 for the first monitoring standard and a value of 1 for the second monitoring standard; β0 is the initial intercept of the first monitoring standard, and β1 is the intercept offset of the second monitoring standard relative to the first monitoring standard. The time drift slope shared by the two standards. This is the residual term.

[0083] The time drift slope is obtained by solving the fitted model based on the monitoring data. .

[0084] Step S4: Using the time drift slope, perform time drift correction on all data points of all analytical standards and unknown samples to obtain... 34 S / 32 S-leveling value; and based on 34 S / 32 S-leveling value, calculate δ for each analytical standard and unknown sample. 34 S-leveling value and instrument mass fractionation IMF leveling value.

[0085] In this step, based on the time drift slope Time drift correction is applied to each data point using the following formula:

[0086] (2)

[0087] In equation (2), The serial number of the test point; Indicates the first test points 34 S / 32 S ratio, Indicates the first After time drift correction at each test point 34 S / 32 S-leveling value, The time drift slope is negative, therefore -k(i-1) is positive. This is because in apatite sulfur isotope analysis... 34 S / 32 The S ratio is typically close to 0.04, while the sequence number i can reach tens or hundreds. The difference in magnitude between the two is significant, and direct linear correction would lead to numerical distortion. Therefore, the measured ratio is magnified by 1000 times to bring it to the same order of magnitude as the sequence number, thereby eliminating time drift through linear correction; then, it is divided by 1000 to restore the original dimensions.

[0088] like Figure 4 As shown, after calibration, the same standard sample measured at different times... 34 S / 32 The S-ratio tends to stabilize, indicating that the time drift correction is effective; all subsequent δ 34 The calculation of S is based on the corrected 34 S / 32 S ratio, i.e. 34 S / 32 S-leveling value. δ 34 The formula for calculating the S-leveling value is as follows:

[0089] (3)

[0090] In equation (3), Indicates the first δ at each test point 34 S-leveling value; ( 34 S / 32 S) V-CDT The international standard for representing sulfur isotope ratios (Vienna Canyon Diablo Troilite, V-CDT) has a ratio of 0.044163.

[0091] Based on each analytical standard and each test point 34 S / 32 S-leveling value and analytical standard 34 S / 32 The S-recommended value is used to calculate the IMF balancing value, using the following formula:

[0092] = (4)

[0093] In equation (4), This represents the test point sequence number corresponding to the r-th analytical standard sample in the test point sequence {1,2,…,j,…,M}. This represents the r-th analytical standard. 34 S / 32 S recommended value.

[0094] Step S5, to analyze the standard sample34 S / 32 The S-leveling value is the independent variable, and the IMF-leveling value is the dependent variable. An instrument fractionation relationship is constructed for each analytical standard, and the first slope and first intercept are obtained by solving. The first slope is the same for all leveling relationships, but the first intercept differs for different analytical standards. Then, using the analytical standard... 34 S / 32 With S-leveling as the independent variable and the first intercept as the dependent variable, the intercept relationship of all analytical standards is constructed, and the second slope and the second intercept are obtained by solving.

[0095] In this step, the balancing formula for each analytical standard is as follows:

[0096] = (5)

[0097] In equation (5), k1 is the first slope shared by all standards, reflecting the common law of matrix effect on IMF; b1 is the first intercept unique to each standard, representing the degree to which each standard deviates from the common law due to compositional differences.

[0098] like Figure 5 As shown in Figure A, k1 is the same for all analytical standards, reflecting the common pattern of matrix effects on IMF, while b1 is different, representing the degree to which each standard deviates from the common pattern due to component differences; the intercepts b1 of different standards are adjusted for time. 34 S / 32 The S ratios exhibit a good linear correlation. Therefore, based on different intercepts b1, a correlation was established between the S ratio and the balanced S ratio. 34 S / 32 The linear relationship between S ratios, such as Figure 5 As shown in B, the constructed intercept relationship is as follows:

[0099] (6)

[0100] In equation (6), k2 is the second slope and b2 is the second intercept. All analytical standards lie on the same linear fitting line and share a common second slope and second intercept.

[0101] Combining formulas (5) and (6), we can obtain the formula for calculating the IMF leveling value of each unknown sample:

[0102] = (7)

[0103] For the same analysis process, we have:

[0104] (8)

[0105] In equation (8), This represents the test point sequence number corresponding to the s-th unknown sample in the test point sequence {1,2,…,j,…,M}.

[0106] Step S6: Based on the first slope, the second slope, and the second intercept, construct a formula for calculating the recommended value after matrix effect correction; substitute the test data of the unknown sample into the formula for calculating the recommended value to obtain the δ of the unknown sample. 34 S-value.

[0107] In this step, the formula for calculating the recommended value after matrix effect correction is as follows:

[0108] (9)

[0109] In equation (9), For the s-th unknown sample, based on time-balanced... 34 S / 32 S ratio, δ after leveling the s-th unknown sample 34 S-value, k1, k2 and b2 are constants obtained by fitting the standard sample.

[0110] Sly-1 was used as a high-sulfur isotope standard, Durango-A as a low-sulfur isotope standard, and SAP-1 as an intermediate-value standard. Durango-B, MG, OL-1, Big1, and Mdg-1 were used as test samples to verify the method described in this invention. After target preparation, SIMS sulfur isotope analysis was performed on all standards to obtain... 32 S and 34 The test value of S; time drift correction is applied to the test value to obtain the leveled value. Determine the k1 and b1 of each of the three analytical standards; based on the b1 determined by the three standards and the time-balanced... 34 S / 32 A linear function was established using the S ratio to determine k2 and b2; finally, the sulfur isotope value δ of the test sample was calculated. 34 S. Calculate δ 34 The S-value was compared with the recommended value, and the corrected δ 34 The S-value and the recommended value are consistent within the error range, with the absolute value of the deviation being less than 0.7‰.

[0111] This invention establishes time-leveling after 34 S / 32 The functional relationship between the S ratio and IMF enables the determination of the δ of unknown samples. 34 High-precision correction of the S-value. Under high spatial resolution conditions of a 10 μm beam spot (superior to previous 15 μm beam spots), apatite δ... 34The S ratio can be accurate to within 0.8‰, and the analytical precision (2SD) of each standard sample is generally better than that of previous studies. This method has achieved good correction results in multiple published SIMS datasets. Based on correction practice, it is recommended to use standard combinations with low, medium, and high sulfur isotope endmembers (such as Sly-1, Durango-A / Durango-B, and OL-1 / SAP1 / Big1) for analysis and correction.

[0112] As can be seen from the above technical solutions, the matrix correction method and sulfur content determination method based on SIMS analysis of apatite sulfur isotopes described in the embodiments of the present invention do not introduce a primary standard-secondary standard system at all. Instead, they directly utilize the instrument mass fractionation (after IMF balancing) of each apatite standard sample after time-balanced analysis with its own content. 34 S / 32 The correlation between the S ratio and the standard sample is corrected. Specifically, this invention first establishes the correlation between the IMF-balanced and standard sample values ​​of each standard sample and the standard sample. 34 S / 32 The linear relationship after S-leveling (Formula 5) was then used to discover the intercept (b1) of different standard samples in this relationship and its relationship with 34 S / 32 After S is balanced, a quadratic linear relationship exists (Equation 6), which ultimately leads to the direct calculation of δ for unknown samples. 34 The closed-loop formula for S (Formula 9). The entire correction process is based on the absolute value of the IMF of the standard sample itself, rather than the relative difference. The mathematical path and variable definitions are completely different from the pyrrhotite method. Therefore, the latter cannot be directly applied to the matrix effect correction of apatite.

[0113] It should be understood that, in various embodiments of the present invention, the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0114] The above description is merely a preferred embodiment of the present invention and an explanation of the technical principles employed, and is not intended to limit the scope of the claimed invention, but merely to illustrate preferred embodiments of the invention. Those skilled in the art should understand that the scope of the invention is not limited to the specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the inventive concept. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

Claims

1. A matrix correction method for apatite sulfur isotope micro-area analysis based on SIMS, characterized in that, The method includes the following steps: Step S1: Collect at least three different in-situ sulfur isotope analysis standards for apatite micro-regions; prepare a sample target, wherein the sample target includes the analysis standards and the unknown sample to be tested; Step S2: Select at least two analytical standards as monitoring standards simultaneously; use the SIMS method to test the sulfur isotope signals of the analytical standards, the unknown sample, and the monitoring standards on the sample target; the sulfur isotope signals include... 34 The count rate of S and 32 The count rate of S; Step S3: Using a linear regression model with grouping variables, all data points of the monitoring standard are jointly fitted, and the time drift slope is obtained by solving the fitted model. Step S4: Using the time drift slope, perform time drift correction on all data points of all analytical standards and unknown samples to obtain... 34 S / 32 S-leveling value; and based on 34 S / 32 S-leveling value, calculate δ for each analytical standard and unknown sample. 34 S-leveling value and instrument mass fractionation IMF leveling value; Step S5, to analyze the standard sample 34 S / 32 The S-leveling value is the independent variable, and the IMF-leveling value is the dependent variable. An instrument fractionation relationship is constructed for each analytical standard, and the first slope and first intercept are obtained by solving. The first slope is the same for all leveling relationships, but the first intercept differs for different analytical standards. Then, using the analytical standard... 34 S / 32 With S-leveling as the independent variable and the first intercept as the dependent variable, the intercept relationship of all analytical standards is constructed, and the second slope and the second intercept are obtained by solving. Step S6: Based on the first slope, the second slope, and the second intercept, construct a formula for calculating the recommended value after matrix effect correction; substitute the test data of the unknown sample into the formula for calculating the recommended value to obtain the δ of the unknown sample. 34 S-value.

2. The method according to claim 1, characterized in that, The preparation of the sample target includes: Step S11: Prepare glass slides of the predetermined size and apply double-sided tape; arrange each standard sample in a row according to the order of particle size from largest to smallest, and stick them in a circle with a diameter of about 1 cm on the double-sided tape; arrange the analytical standard samples and unknown samples in order from top to bottom; Step S12: Place the smooth polyethylene hollow column vertically on the double-sided adhesive, ensuring that the circular part of the sample is centered in the polyethylene hollow column; slowly inject the mixture of epoxy resin and coagulant after vacuuming along the inner surface of the polyethylene hollow column, vacuum again and let it stand to allow the mixture to solidify, obtaining a solidified sample sheet that can be removed from the polyethylene hollow column; use fine sandpaper and a polishing pad to polish the sample sheet in sequence, so that both the analytical standard and the unknown sample to be tested are exposed on one side of the sample sheet. Step S13: Clean the sample slices; Step S14: Deposit conductive material to obtain sample target.

3. The method according to claim 1, characterized in that, The testing process using the SIMS method in step S2 is as follows: Let the number of analytical standard samples be Q1, the number of unknown samples be Q2, and the number of monitoring standard samples be Q3; and 2≤Q3≤Q1; After setting the test parameters, the Q1 analytical standards are tested sequentially in a forward order, with each standard tested at P1 consecutive points. Next, the Q2 unknown samples are tested, with each monitoring standard sample's test point inserted at intervals of P2 unknown sample test points within the unknown sample test sequence. At the end of the unknown sample testing, each analytical standard sample is tested again in a reverse order, with P1 consecutive points tested. This process is repeated for all analytical standards, unknown samples, and monitoring standards, yielding all analytical points for all samples. 34 S and 32 The count rate of S.

4. The method according to claim 1, characterized in that, When two monitoring standards are used in step S3, the fitting model for the joint fitting is as follows: ，(1) In equation (1), For the first The first monitoring standard sample test points 34 S / 32 S ratio; The indicator variable is the monitoring standard, with a value of 0 for the first monitoring standard and a value of 1 for the second monitoring standard; β0 is the initial intercept of the first monitoring standard, and β1 is the intercept offset of the second monitoring standard relative to the first monitoring standard. The time drift slope shared by the two standards. This is the residual term.

5. The method according to claim 4, characterized in that, Based on time drift slope Time drift correction is applied to each data point using the following formula: ，(2) In equation (2), The serial number of the test point; Indicates the first test points 34 S / 32 S ratio, Indicates the first After time drift correction at each test point 34 S / 32 S-leveling value.

6. The method according to claim 1, characterized in that, The δ 34 The formula for calculating the S-leveling value is as follows: ，(3) In equation (3), Indicates the first δ at each test point 34 S-leveling value; International standard for representing sulfur isotope ratios.

7. The method according to claim 1, characterized in that, The formula for calculating the IMF leveling value is as follows: Based on each analytical standard and each test point 34 S / 32 S-leveling value and analytical standard 34 S / 32 The S-recommended value is used to calculate the IMF balancing value, using the following formula: = ，(4) In equation (4), This represents the test point sequence number corresponding to the r-th analytical standard sample in the test point sequence {1,2,…,j,…,M}. This represents the r-th analytical standard. 34 S / 32 S recommended value.

8. The method according to claim 1, characterized in that, In step S5, the instrument fractionation relationship for each analytical standard is as follows: = ，(5) In equation (5), k1 is the first slope shared by all standards, reflecting the common law of matrix effect on IMF; b1 is the first intercept unique to each standard, representing the degree to which each standard deviates from the common law due to compositional differences. The intercept relationship is as follows: ，(6) In equation (6), k2 is the second slope and b2 is the second intercept.

9. The method according to claim 1, characterized in that, The IMF leveling value for each unknown sample is calculated using the following formula: = ，(7) The formula for calculating the recommended value for an unknown sample is as follows: ，(8) In equation (8), This represents the test point sequence number corresponding to the s-th unknown sample in the test point sequence {1,2,…,j,…,M}.

10. The method according to claim 1, characterized in that, The formula for calculating the recommended value after matrix effect correction is as follows: ，(9) In equation (9), This represents the test point sequence number corresponding to the s-th unknown sample in the test point sequence {1,2,…,j,…,M}; For the s-th unknown sample, based on time-balanced... 34 S / 32 S ratio, δ after leveling the s-th unknown sample 34 S value, k1, k2 and b2 are the first slope, second slope and second intercept obtained by solving, respectively.

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