A method for determining the content of carbonate minerals

Abstract

The application discloses a kind of carbonate mineral content determination method, belong to the technical field of process mineralogy.The method is prepared by carbonate mineral powder and matrix mineral powder gradient standard sample, the cross-sectional area proportion of carbonate mineral in each standard sample is obtained using automatic mineralogical analysis system, and the working curve of area proportion and mass fraction is established;After the same sample preparation and analysis are carried out to the ore sample to be measured, the measured area proportion is substituted into the working curve to obtain the apparent carbonate mineral mass fraction, and based on the density relationship between carbonate mineral and matrix mineral, a comprehensive correction coefficient is introduced for density correction, and finally the actual mass fraction is output.The application eliminates matrix effect by matching matrix, compensates stereology deviation by density correction, solves the technical problem that area proportion cannot be directly equivalent to mass fraction in traditional automatic mineralogical quantification, and has the advantages of wide determination range, high accuracy and suitability for complex multi-carbonate ore system.

Description

Technical Field

[0001] This invention relates to the field of process mineralogy, specifically to a method for determining the content of carbonate minerals. Background Technology

[0002] Accurate determination of carbonate mineral content is of great significance in geological exploration, mineral processing control, and building material quality evaluation. Carbonate minerals (represented by calcite and dolomite) are widely distributed, and their content directly affects the industrial value of ore, the selection of beneficiation and smelting processes, and the quality of subsequent products.

[0003] Currently, methods for determining carbonate mineral content mainly include chemical analysis, thermogravimetric analysis, X-ray diffraction (XRD) quantitative analysis, and infrared spectroscopy. While chemical analysis methods (such as acid-base titration) offer high precision, they are cumbersome, time-consuming, and require large amounts of chemical reagents, making them unsuitable for rapid detection of large batches of samples. Thermogravimetric analysis estimates carbonate content based on the mass loss of CO2 released during thermal decomposition, but the equipment is expensive, and the presence of other volatile components (such as organic matter and water of crystallization) in the sample can significantly interfere with the results. X-ray diffraction quantitative analysis (such as RIR and full-spectrum fitting methods) is affected by mineral crystal orientation and micro-absorption effects, often resulting in insufficient quantitative accuracy, especially when carbonate mineral content is low, where errors increase significantly.

[0004] In recent years, automated mineralogical analysis systems (such as MLA, QEMSCAN, TIMA, AMICS, BPMA, etc.) have been widely used in quantitative mineral research due to their advantages of speed, automation, and strong statistical representativeness. These systems, based on backscattered electron image (BSE) grayscale recognition combined with energy dispersive spectroscopy (EDS) component verification, can quickly obtain process mineralogical parameters such as the area ratio, degree of liberation, and particle size distribution of mineral particles. However, when directly applying automated mineralogical analysis systems to determine the content of carbonate minerals, the following technical problems still need to be addressed: First, the reliability of mineral phase identification is poor. The average atomic number differences between carbonate minerals such as calcite, dolomite, siderite, magnesite, and aragonite, and between them and gangue minerals such as quartz, feldspar, fluorite, and apatite, are small, resulting in high overlap of BSE grayscale values ​​and making effective differentiation difficult. EDS has low detection efficiency for ultralight elements such as carbon, making it unreliable as a sole criterion. Second, exogenous carbon interference is severe. Sample preparation requires the spraying of a carbon film, introducing exogenous carbon. The thickness and uniformity of this film, as well as fluctuations in analytical conditions, significantly affect the carbon peak intensity, interfering with spectrum matching and background subtraction. The problems with carbonate microparticle contamination or its association with clay and ferruginous mud are significant. Furthermore, carbonates are susceptible to radiation damage under electron beam bombardment, leading to spectral drift and further reducing the stability of compositional verification. Thirdly, there is a lack of targeted density correction for area fraction and mass content. The system measures area fraction, which must be converted using actual density weighting. Existing methods often use theoretical density or default values, failing to consider isomorphous substitution, solid solution variations, and the effects of micropores and inclusions. Significant deviations occur when carbonate content is low or the density of associated minerals differs greatly. Fourthly, there is a lack of matrix-matched standard materials. Existing standard materials differ significantly from real samples in mineral assemblage, particle size distribution, and content gradient, resulting in poor applicability of calibration curves, insufficient data comparability between laboratories, and difficulty in achieving traceability and uncertainty assessment.

[0005] In view of this, there is an urgent need to establish a method for determining carbonate mineral content that can effectively eliminate the interference of exogenous carbon and accurately identify carbonate minerals, so as to meet the needs of accurate, rapid and traceable determination of carbonate content in process mineralogy research and mineral resource evaluation. Summary of the Invention

[0006] In view of the technical problems existing in the background art, the present invention provides a method for determining the content of carbonate minerals. By using standard samples and materials with good matrix matching, the matrix effect is eliminated, density correction is introduced to improve the quantitative accuracy, the working curve corresponding to the preparation of multiple standard samples has excellent linearity, the determination range is flexible, and it is applicable to complex ore systems in which multiple carbonate minerals coexist. It has good versatility and engineering application value.

[0007] This invention provides a method for determining the content of carbonate minerals, which includes the following steps: S1. Preparation of standard samples: Carbonate mineral powder and matrix mineral powder are mixed and dispersed evenly in different mass fractions to prepare multiple sets of standard samples; wherein the matrix minerals and the main gangue minerals in the ore sample to be tested belong to the same type of minerals; S2. Standard Sample Analysis: Perform automated mineralogical analysis on each group of standard samples to obtain the area ratio of carbonate minerals in each standard sample; S3. Construction of working curve: Construct a working curve of carbonate mineral content with the mass fraction of carbonate minerals in each standard sample as the ordinate and the corresponding area percentage measured in step S2 as the abscissa. S4. Analysis of the ore sample to be tested: Perform automatic mineralogical analysis on the ore sample to be tested to obtain the area ratio of carbonate minerals in the ore sample; calculate the theoretical density of the ore sample to be tested based on the relative volume content and theoretical density of each carbonate mineral in the ore sample to be tested. S5. Calculation of carbonate mineral content: Based on the theoretical density of the ore sample to be tested, the theoretical density of carbonate minerals, and the working curve constructed in step S3, the apparent carbonate mineral content determined by the area ratio of the ore sample to be tested is corrected for density to obtain the actual carbonate mineral content.

[0008] As a further improvement of the present invention, in step S5, the density correction satisfies the following relationship: Cm 实际 =Cm'×K0×ρm / ρ; Among them, Cm 实际 Let Cm' be the actual mass fraction of the m-th carbonate mineral, Cm' be the apparent mass fraction of the carbonate mineral obtained from the area ratio of the ore sample to be tested based on the working curve, K0 be the comprehensive correction coefficient, ρm be the theoretical density of the m-th carbonate mineral, and ρ be the theoretical density of the ore sample to be tested.

[0009] As a further improvement of the present invention, in step S4, the theoretical density ρ of the ore sample to be tested is Σ(an×ρn), where an is the volume relative content of the nth mineral in the ore sample to be tested as determined by automatic mineralogical analysis, and ρn is the theoretical density of the nth mineral.

[0010] As a further improvement of the present invention, the comprehensive correction coefficient K0 = 0.5 × (ρ 基体矿物 +ρ 碳酸盐矿物 ) / ρ 碳酸盐矿物 ; Where, ρ 基体矿物 ρ is the density of the matrix minerals. 碳酸盐矿物 Density corresponding to a specific type of added carbonate mineral; When the matrix mineral is quartz and the carbonate mineral is calcite, K0 = 0.9907.

[0011] As a further improvement of the present invention, in step S3, the least square method is used for linear fitting or conic fitting to obtain a working curve regression equation, and the correlation coefficient R²≥0.995; the expression of the working curve regression equation is as follows: When 0.01<b or b<-0.01, C=k × A × 100+ b; Or, when -0.01≦b≦0.01, C=k1 × (A× 100) 2 +k2 ×(A× 100) +e; Wherein, C is the mass fraction of the carbonate mineral, A is the area proportion of the carbonate mineral, k is the slope, k1 and k2 are coefficients, b is the intercept, and e is the intercept.

[0012] As a further improvement of the present invention, in step S5, the expression of the apparent carbonate mineral mass fraction Cm' is as follows: When -0.01≦b≦0.01, Cm'=k × Am 待测 × 100+ b; Or, when 0.01<b or b<-0.01, Cm'=k1 × (Am 待测 × 100) 2 +k2 × Am 待测 × 100+e; Wherein, Am 待测 is the area proportion of the m-th carbonate mineral in the ore sample to be tested.

[0013] As a further improvement of the present invention, in step S1, the multiple groups of standard samples are no less than 5 groups, the different mass fraction ratios cover the carbonate mineral mass fraction range of 0.5% to 90%, and at least include gradients of a low content interval, a medium content interval and a high content interval.

[0014] As a further improvement of the present invention, in step S1, the matrix mineral is at least one of quartz, feldspar, mica, amphibole and pyroxene, and the carbonate mineral component is at least one of calcium carbonate, magnesium carbonate and zinc carbonate.

[0015] As a further improvement of the present invention, in step S1, the specific steps of mixing and uniformly dispersing include: placing the carbonate mineral powder and the matrix mineral powder in a ball mill, using absolute ethanol as a grinding aid, performing ball milling and mixing at a rotational speed of 200 to 300 r / min according to the mass ratio of material, ball and ethanol of 1:(4~6):(0.5~0.8), until all the mixture passes through a 200-mesh standard sieve.

[0016] As a further improvement of the present invention, it is applicable to complex ore systems containing two or more carbonate minerals. Steps S1 to S5 are performed for each carbonate mineral to establish working curves and perform density correction of apparent carbonate mineral mass fraction.

[0017] Beneficial effects: 1. This invention establishes a linear working curve of carbonate area ratio and mass fraction, enabling rapid and batch calibration of carbonate mineral area content, effectively reducing the error of X-ray peak identification.

[0018] 2. The present invention introduces a density correction step, which effectively eliminates the systematic bias of the quantitative results of the area ratio caused by the difference in the density of different ore matrices, making the measurement results closer to the true mass fraction, and the relative error can be controlled within ±3%.

[0019] 3. This invention uses artificially synthesized standard samples with quartz as the dilution matrix. Quartz has stable chemical properties and does not interfere with the determination of carbonate minerals in automated mineralogical analysis. Moreover, it is consistent with the main gangue components in most ores. The standard sample is highly matched with the matrix of the ore to be tested, effectively overcoming the matrix effect of the traditional powder pressing method.

[0020] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and in order to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0021] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the present invention will be briefly described below. Obviously, the drawings described below are merely some embodiments of the present invention, and those skilled in the art can obtain other drawings based on these drawings without any creative effort.

[0022] Figure 1 This is a schematic flowchart of the method for determining the carbonate mineral content provided in an embodiment of the present invention. Detailed Implementation

[0023] The embodiments of the technical solution of the present invention will now be described in detail with reference to the accompanying drawings. These embodiments are merely illustrative of the technical solution of the present invention and are therefore intended to limit the scope of protection of the present invention.

[0024] 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 invention pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the invention; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the invention, are intended to cover non-exclusive inclusion.

[0025] In the description of the embodiments of this invention, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this invention, "multiple" means two or more, unless otherwise explicitly defined.

[0026] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0027] In the description of the embodiments of this invention, the term "and / or" 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, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0028] In the description of the embodiments of the present invention, the term "multiple" refers to two or more (including two), similarly, "multiple groups" refers to two or more (including two groups), and "multiple pieces" refers to two or more (including two pieces).

[0029] To address the limitations of existing technologies in the quantitative characterization of carbonate minerals, such as the overlap of BSE grayscale between minerals, the limitations of EDS light element detection, the interference of exogenous carbon introduced by carbon films in sample preparation, the area-mass density correction deviation due to the lack of consideration for practical factors such as isomorphism, and the lack of matrix-matching standard materials, which lead to difficulties in effectively distinguishing carbonate minerals, poor stability in component verification, inaccurate content conversion, and difficulties in traceability of values, this invention provides a method for determining the content of carbonate minerals. By preparing a series of standard samples using quartz as the matrix-matching material, and establishing a working curve of area percentage versus mass fraction using automated mineralogical analysis, and by introducing a comprehensive density correction coefficient, this method solves the technical problem of the influence of matrix effects and density deviations on the quantitative analysis of carbonate minerals in complex ore systems, and achieves accurate determination of the mass content when multiple carbonate minerals coexist.

[0030] Please refer to Figure 1 As shown, this embodiment of the invention provides a method for determining the content of carbonate minerals, including the following steps: S1. Preparation of Standard Samples S11. Prepare high-purity (≥99.90%) calcium carbonate powder and quartz powder, dry them separately in an oven at 100℃±2℃ to constant weight, and cool them in a desiccator for later use.

[0031] S12. According to the proportions shown in Table 1 (which can be modified according to actual application conditions, or the spot density can be increased specifically), accurately weigh calcium carbonate and quartz powder to prepare at least 5 gradient standard samples, wherein the mass fraction of carbonate (calcium carbonate) is Ci.

[0032] Table 1 Standard Sample Configuration Table S13. Place each sample in a planetary ball mill (material, ball, ethanol mass ratio of 1:4~6:0.5~0.8), and ball mill at 200~300 r / min with anhydrous ethanol as grinding aid to ensure that calcium carbonate is uniformly dispersed in the quartz matrix until all of it passes through a 200 mesh standard sieve (-0.074 mm).

[0033] S2, Automated Mineralogical Analysis of Standard Samples S21. Take 3.0–5.0 g of each standard sample obtained in step S1 and prepare automated mineralogical analysis sample blocks using the epoxy resin embedding method. Specifically, mix the standard sample with an epoxy resin and curing agent mixture at a solid-liquid ratio of 1:2–1:3, ultrasonically vibrate for 15–20 minutes, and cure at room temperature for 12–24 hours. Grind and polish the cured sample blocks sequentially using 200-grit, 500-grit, 1000-grit, and 2000-grit silicon carbide sandpaper, and finally polish with 0.5–1.0 μm diamond polishing agent until the surface is smooth and free of scratches. Place the polished sample blocks in a vacuum coating apparatus and spray an 8–15 nm carbon film onto the surface.

[0034] S22. Use an automated mineralogical analysis system to measure the standard samples. Set the BSE image resolution to 0.5~1.0μm / pixel and collect no less than 5000 particles for each standard sample.

[0035] Record the area percentage Ai of calcium carbonate minerals in each standard sample.

[0036] S3, Establishing the Working Curve A working curve was established, with the amount of calcium carbonate added (Ci) on the ordinate and the measured area ratio of calcium carbonate (salt) minerals (Ai) on the abscissa. A linear fit was performed using the least squares method to obtain the regression equation for the working curve: When 0.01<b or b<-0.01, C=k × A × 100+ b; Alternatively, when -0.01≦b≦0.01, C=k1 × (A× 100) 2 +k2 ×(A× 100) +e; wherein, C is the mass fraction of carbonate minerals, A is the area proportion of carbonate minerals, k is the slope, k1 and k2 are coefficients, b is the intercept, and e is the intercept.

[0037] It is required that the correlation coefficient R² of the working curve is ≥0.995, otherwise the standard sample needs to be re-prepared and measured.

[0038] S4. Treatment of the test sample and automatic mineralogical analysis S41. Take 200~500g of the test ore sample, crush it until all passes through a 2mm sieve, and reduce it to 50~100g by the quartering method. The reduced sample is ground in a planetary ball mill until all passes through a 200-mesh standard sieve (0.074mm), and dried in an oven at a temperature below 100℃ for 4 hours to constant weight. Weigh 3.0~5.0g to prepare an automatic mineralogical analysis sample block, and the preparation conditions are the same as those in step S2.

[0039] S42. Using the same instrument parameters and measurement conditions as in step S2, perform automatic mineralogical analysis on the test sample, and collect no less than 8000 particles for each sample.

[0040] The measured area proportion Am of the m-th carbonate mineral 待测 , 3 parallel sample blocks are prepared for each sample repeatedly, each parallel sample block is measured independently, and the average value of the 3 measurement results is taken as the calcium carbonate area proportion of this type. Calculate the relative standard deviation RSD of the three measurement results. If RSD>5%, the sample needs to be re-prepared and measured.

[0041] S43. Calculation of the theoretical density of the sample. The volume relative content of the n-th mineral measured by automatic mineralogical analysis is an. The theoretical density ρ of the test ore sample is ρ=Σ(an×ρn), wherein, an is the volume relative content of the n-th test mineral in the test ore sample measured by automatic mineralogical analysis, and ρn is the theoretical density of the n-th test mineral. The n test minerals in the test ore sample include non-carbonate minerals and carbonate minerals.

[0042] S5. Calculation of calcium carbonate content S51. Substitute the area proportion Am of each type of carbonate mineral 待测 into the working curve to obtain the apparent carbonate mineral mass content measurement value Cm' based on the quartz matrix, then When -0.01≦b≦0.01, Cm'=k × Am待测 × 100 + b; Alternatively, when 0.01 < b or b < -0.01, Cm' = k1 × (Am 待测 × 100) 2 + k2 × Am 待测 × 100 + e.

[0043] S52. Density correction: Cm 实际 = Cm' × 0.9907 × ρm / ρ, where m is the number of different carbonate species; 0.5 × (ρ 石英 + ρ 方解石 ) / ρ 方解石 = 0.5 × (2.65 + 2.70) / 2.70 = 0.9907, which is a comprehensive correction factor (taking into account the systematic deviation in the preparation and measurement process of standard samples, the density deviation of different standard sample ratios, etc.). The new mass ratio is converted through the fixed value density and area. The density needs to comprehensively consider the ratio of quartz and calcium carbonate (the main component of calcite) in different proportions, so an average value of 0.5 times is taken, which has wide applicability.

[0044] It should be noted that: the matrix minerals can also be feldspar, mica, amphibole, and pyroxene, and the carbonate mineral components can also be calcium carbonate, magnesium carbonate, zinc carbonate, etc.

[0045] Example 1 Example 1 of the present invention provides a method for determining the content of carbonate minerals, which is specifically applied to the determination of the content of carbonate minerals in a certain gold ore, comprising the following steps: S1. Standard sample preparation S11. Prepare high-purity (≥99.9%) calcium carbonate powder and quartz powder, dry them in an oven at 100°C to constant weight respectively, and place them in a desiccator for cooling for later use.

[0046] S12. Prepare 5 standard samples P1 to P5 according to the ratio shown in Table 2, where the mass fraction of carbonate is Ci; S13. After accurately weighing each component, perform ball milling for 0.20 hours at a rotation speed of 250 r / min according to a material-ball-ethanol ratio of 1:5:0.6, dry and pass through a 200-mesh sieve for later use.

[0047] Table 2 Standard sample configuration table S2. Automatic mineralogical analysis of standard samples S21. Take 4.0 g of each standard sample obtained in step S1 and prepare automated mineralogy analysis sample blocks using the epoxy resin embedding method. Specifically, mix the standard sample with the epoxy resin and curing agent mixture at a solid-liquid ratio of 1:2, ultrasonically vibrate for 15 minutes, and cure at room temperature for 12 hours. Grind and polish the cured sample blocks sequentially using 200-grit, 500-grit, 1000-grit, and 2000-grit silicon carbide sandpaper, and finally polish with 0.5~1.0μm diamond polishing agent until the surface is smooth and free of scratches. Place the polished sample blocks in a vacuum coating instrument and spray a 10nm carbon film onto the surface.

[0048] S22. Use an automated mineralogical analysis system to measure the standard samples. Set the BSE image resolution to 0.5 μm / pixel and collect no less than 5,000 particles for each standard sample.

[0049] Record the area percentage Ai of calcium carbonate minerals in each standard sample, as detailed in Table 3.

[0050] Table 3 Results of Automated Mineralogical Analysis of Standard Samples S3, Establishing the Working Curve A working curve was established, with the amount of calcium carbonate added (Ci) on the ordinate and the measured carbonate area percentage (Ai) on the abscissa. A linear fit was performed using the least squares method to obtain the regression equation for the working curve: C=1.0673 × A -0.107, R²=0.9991; The relative standard deviation (RSD) of multiple results was 1.32% ≤ 5.00%, indicating that the standard sample had good homogeneity.

[0051] S4. Sample preparation and automated mineralogical analysis S41. Take 500g of the ore sample to be tested, crush it until it all passes through a 2mm sieve, and reduce it to 100g using the quartering method. Grind the reduced sample in a planetary ball mill until it all passes through a 200-mesh standard sieve (0.074mm), and dry it in an oven below 100℃ for 4 hours until constant weight. Weigh 4.0g to prepare an automated mineralogical analysis sample block, using the same preparation conditions as in step S2.

[0052] S43. Using the same instrument parameters and measurement conditions as in step S2, perform automated mineralogical analysis on the sample to be tested, collecting no less than 8,000 particles for each sample.

[0053] The area percentage Am of the m-th carbonate was measured. 待测 Three parallel samples were prepared for each sample, and each parallel sample was measured independently. The average of the three measurements was taken as the area ratio of calcium carbonate of that type.

[0054] S43. Theoretical density calculation of the sample, and automated mineralogical analysis are detailed in Table 4.

[0055] Table 4 Results of automated mineralogical analysis of the samples to be tested The theoretical density of the sample is ρ = Σ(an×ρn). =0.1148+0.0420+1.4909+……+0.0021+0.3307 =2.75 g / cm³.

[0056] S5. Calculation of calcium carbonate content S51, the area percentage of various types of carbonate minerals Am 待测 Substituting the values ​​into the working curve, we obtain the apparent carbonate mass fraction measurement value Cm' based on the quartz matrix. Calcite: C1' = 1.0673 × A1 × 100 - 0.107 = 1.0673 × 4.78 - 0.107 = 4.99%, Siderite: C2'=1.0673 × A2×100-0.107=1.0673 × 1.09-0.107=1.06%; S52, Density Correction: C1 实际 =C1' × 0.9907 × ρm / ρ=4.99% × 0.9007 × 2.70 / 2.75=4.41%; C2 实际 =C2' × 0.9907 × ρm / ρ=1.06% × 0.9007 × 3.96 / 2.75=1.38%.

[0057] Verification: Through multiple measurements, the error deviation was less than 2%, and the data fluctuation was small. Further verification using chemical analysis methods (such as acid-base titration) showed good data consistency.

[0058] Example 2 Example 2 of this invention provides a method for determining the content of carbonate minerals, specifically applied to the determination of high-content carbonate minerals in a lead-zinc polymetallic ore, comprising the following steps: S1. Preparation of Standard Samples S11. Prepare high-purity (≥99.9%) calcium carbonate powder and quartz powder, dry them separately in an oven at 100℃ to constant weight, and cool them in a desiccator for later use.

[0059] S12. Prepare five standard samples P1 to P5 according to the proportions shown in Table 2, wherein the mass fraction of carbonate is Ci. S13. After accurately weighing each component, ball mill them at a ratio of 1:5:0.6 (material, ball, ethanol) for 0.20 hours at 250 r / min. After drying, pass the mixture through a 200 mesh sieve for later use.

[0060] Table 5 Standard Sample Configuration Table S2, Automated Mineralogical Analysis of Standard Samples Following the same procedure, record the area ratio Ai of calcium carbonate minerals in each standard sample, as detailed in Table 6.

[0061] Table 6 Results of Automated Mineralogical Analysis of Standard Samples S3, Establishing the Working Curve A working curve was established, with the amount of calcium carbonate added (Ci) on the ordinate and the measured carbonate area percentage (Ai) on the abscissa. A linear fit was performed using the least squares method to obtain the regression equation for the working curve: C = 1.0022 × A × 100 + 0.0323, b = 0.0323 falls within the range of -0.01 ≤ b ≤ 0.01. Then C = k1 × (A × 100) 2 +k2 × A×100 +e=-3 × 10 -5 × (A×100) 2 +1.0051 × (A × 100) -0.015 The relative standard deviation (RSD) of multiple results was 1.01% ≤ 5.00%, indicating that the standard sample had good homogeneity.

[0062] S4. Sample preparation and automated mineralogical analysis Same as before, S43. Theoretical density calculation of the sample, and automated mineralogical analysis are detailed in Table 7.

[0063] Table 7 Results of automated mineralogical analysis of the samples to be tested The theoretical density of the sample is ρ = Σ(an×ρn). =0.5983+1.0738+……+0.0382+0.5310 =2.90 g / cm³.

[0064] S5. Calculation of calcium carbonate content S51, the area percentage of various types of carbonate minerals Am 待测 Substituting the values ​​into the working curve, we obtain the apparent carbonate mass content measurement value Cm' based on the quartz matrix. Calcite: C1' = -3 × 10 -5 × (A×100) 2 +1.0051 × (A × 100) - 0.015 = -3 × 10 -5 ×25.06 2 +1.0051×25.06-0.015=25.17%, S52, Density Correction: C1 实际 =C1' × 0.9907 × ρm / ρ=25.17% × 0.9007 × 2.70 / 2.75=22.26%.

[0065] In summary, this invention discloses a method for determining carbonate mineral content, belonging to the field of process mineralogy. This method involves preparing gradient standard samples of carbonate mineral powder and matrix mineral powder, using an automated mineralogical analysis system to obtain the cross-sectional area ratio of carbonate minerals in each standard sample, and establishing a working curve of area ratio versus mass fraction. After the same sample preparation and analysis are performed on the ore sample to be tested, the measured area ratio is substituted into the working curve to obtain the apparent mass fraction. Based on the density relationship between carbonate minerals and matrix minerals, a comprehensive correction coefficient is introduced for density correction, ultimately outputting the actual mass content. This invention eliminates matrix effects through matrix matching and compensates for stereochemical bias through density correction, solving the technical problem that area ratio cannot directly equate to mass content in traditional automated mineralogical quantification. It has the advantages of wide measurement range, high accuracy, and applicability to complex multi-carbonate ore systems.

[0066] It should be noted that the present invention is not limited to the above-described embodiments. The above embodiments are merely examples, and any embodiments that have the same structure and perform the same effects as the technical concept within the scope of the present invention are included within the scope of the present invention. Furthermore, various modifications that can be conceived by those skilled in the art to the embodiments, and other ways of constructing by combining some of the constituent elements of the embodiments, without departing from the spirit of the present invention, are also included within the scope of the present invention.

Claims

1. A method for determining the content of carbonate minerals, characterized in that, comprising the following steps: S1. Preparation of standard samples: carbonate mineral powder and matrix mineral powder are mixed according to different mass fraction ratios and dispersed uniformly to prepare multiple groups of standard samples; wherein the matrix mineral is the same type of mineral as the main gangue mineral in the ore sample to be tested; S2. Analysis of standard samples: each group of standard samples is subjected to automatic mineralogical analysis to obtain the area proportion of carbonate minerals in each standard sample; S3. Construction of working curve: the mass fraction of carbonate minerals in each standard sample is taken as the ordinate, and the corresponding area proportion measured in step S2 is taken as the abscissa, so as to construct a working curve for the content of carbonate minerals; S4. Analysis of the ore sample to be tested: the ore sample to be tested is subjected to automatic mineralogical analysis to obtain the area proportion of carbonate minerals in the ore sample to be tested; the theoretical density of the ore sample to be tested is calculated according to the relative volume content of each carbonate mineral in the ore sample to be tested and the theoretical density thereof; S5. Calculation of carbonate mineral content: based on the theoretical density of the ore sample to be tested, the theoretical density of the carbonate minerals and the working curve constructed in step S3, density correction is performed on the apparent mass fraction of carbonate minerals determined from the area proportion of the ore sample to be tested, so as to obtain the actual mass fraction of carbonate minerals.

2. The method for determining carbonate mineral content according to claim 1, characterized in that, In step S5, the density correction satisfies the following relational expression: Cm 实际 =Cm'×K0×ρm / ρ; Among them, Cm 实际 Let Cm' be the actual mass fraction of the m-th carbonate mineral, Cm' be the apparent mass fraction of the carbonate mineral obtained from the area ratio of the ore sample to be tested based on the working curve, K0 be the comprehensive correction coefficient, ρm be the theoretical density of the m-th carbonate mineral, and ρ be the theoretical density of the ore sample to be tested.

3. The method for determining carbonate mineral content according to claim 2, characterized in that, In step S4, the theoretical density ρ of the ore sample to be tested is ρ=Σ(an×ρn), where an is the relative volume content of the nth mineral to be tested in the ore sample to be tested measured by automatic mineralogical analysis, and ρn is the theoretical density of the nth mineral to be tested.

4. The method for determining carbonate mineral content according to claim 2, characterized in that, The comprehensive correction coefficient K0 = 0.5 × (ρ) 基体矿物 +ρ 碳酸盐矿物 ) / ρ 碳酸盐矿物 ; Where, ρ 基体矿物 ρ is the density of the matrix minerals. 碳酸盐矿物 Density corresponding to a specific type of added carbonate mineral; When the matrix mineral is quartz and the carbonate mineral is calcite, K0=0.9907.

5. The method for determining carbonate mineral content according to claim 2, characterized in that, In step S3, the least square method is adopted for linear fitting or conic fitting to obtain the regression equation of the working curve, and the correlation coefficient R²≥0.995; the expression of the regression equation of the working curve is as follows: When 0.01<b or b<-0.01, C=k × A × 100+ b; Alternatively, when -0.01≦b≦0.01, C=k1 × (A× 100) 2 +k2 ×(A× 100) +e; wherein, C is the mass fraction of carbonate minerals, A is the area proportion of carbonate minerals, k is the slope, k1 and k2 are coefficients, b is the intercept, and e is the intercept.

6. The method for determining carbonate mineral content according to claim 5, characterized in that, In step S5, the expression of the apparent mass fraction Cm' of carbonate minerals is as follows: When -0.01≦b≦0.01, Cm'=k × Am 待测 × 100+ b; Alternatively, when 0.01<b or b<-0.01, Cm'=k1 × (Am 待测 × 100) 2 +k2 × Am 待测 × 100+e; Among them, Am 待测 The area percentage of the m-th carbonate mineral in the ore sample to be tested.

7. The method for determining carbonate mineral content according to claim 1, characterized in that, In step S1, the number of the multiple groups of standard samples is no less than 5, the different mass fraction ratios cover the mass fraction range of 0.5% to 90% of carbonate minerals, and at least include gradients of a low content interval, a medium content interval and a high content interval.

8. The method for determining carbonate mineral content according to claim 1, characterized in that, In step S1, the matrix mineral is at least one of quartz, feldspar, mica, amphibole and pyroxene, and the component of the carbonate mineral is at least one of calcium carbonate, magnesium carbonate and zinc carbonate.

9. The method for determining carbonate mineral content according to claim 1, characterized in that, In step S1, the mixing and dispersing uniformly specifically comprises: placing the carbonate mineral powder and the matrix mineral powder in a ball mill, using absolute ethanol as a grinding aid, performing ball milling and mixing at a rotation speed of 200 to 300 r / min according to the mass ratio of material, balls and ethanol of 1:(4~6):(0.5~0.8), until all the mixture passes through a 200-mesh standard sieve.

10. The method for determining carbonate mineral content according to claim 2, characterized in that, It is applicable to complex ore systems containing two or more carbonate minerals. Steps S1 to S5 are performed for each carbonate mineral to establish working curves and perform density correction of apparent carbonate mineral mass fraction.

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