Qualitative identification method for large amount of garnet

Abstract

The invention belongs to the technical field of geology, and particularly relates to a qualitative identification method for a large amount of garnet. The method comprises the following steps that S1, collected garnet particles are washed with clear water and then dried; s2, weighing 2 g of Taile epoxy resin, pouring the Taile epoxy resin into a mold, directly throwing 5-10 g of dried garnet into the Taile epoxy resin, and stirring while pouring the garnet into the Taile epoxy resin; s3, the mold is vacuumized for about 1 h, it is guaranteed that no bubble exists, the mold is put into an oven to solidify the resin, and after the resin is solidified, the resin target is polished and ground till the interiors of sample particles are exposed; s4, testing by using an automatic mineral analysis software instrument; s5, off-line data acquisition, wherein the garnet species information, the total particle number and the content of each kind of garnet in the resin target can be derived off-line from the test data. According to the invention, accurate, efficient and rapid identification of garnet can be realized.

Description

Technical Field

[0001] The invention belongs to the technical field of geology, and in particular relates to a method for qualitatively identifying a large amount of garnets. Background Art

[0002] Garnet crystals are very similar in shape and color to pomegranate seeds, hence the name. Garnet is one of the important silicate minerals in geology, commonly found in metamorphic rocks, and is one of the main rock-forming minerals in the upper mantle. In diamond prospecting, garnet is an important indicator mineral, so a large number of tests and analyses of the chemical composition of garnet are required to identify its isomorphous affiliation. The chemical composition of garnet is relatively complex, and different elements form different combinations, thus forming a series of isomorphous garnet families. Its general formula is A3B2(SiO4)3, where A represents divalent elements (calcium, magnesium, iron, manganese, etc.) and B represents trivalent elements (aluminum, iron, chromium, titanium, vanadium, zirconium, etc.).

[0003] The qualitative identification methods of garnet in the prior art mainly include: ① Optical identification method, which is mainly distinguished according to the appearance color of garnet. The main identification features are shown in Table 1 below. This method is cumbersome and subjective. The quality of the identification depends entirely on the experience of the test personnel. The identification under binoculars and polarizing microscopes only relies on the color and appearance characteristics of the mineral, which is easy to confuse. In addition, optical identification can only obtain a small amount of mineral species information, and it is difficult to obtain specific species information. ② Raman analysis method, Raman spectrum analysis of garnet is performed by Raman spectrometer, and the Raman spectrum is obtained to distinguish different garnet characteristics. However, since there are many isomorphs of garnet, slight changes in the elements will affect the type of garnet. Therefore, the Raman spectrum peaks often overlap, making it difficult to analyze the accurate garnet category. ③ Electron probe analysis method, this method mainly fixes the garnet in the sample stand, and then analyzes it under the electron probe to obtain the main elements of the sample to be analyzed, and then obtain the type characteristics of the garnet. Conventional electron probe analysis methods first require that garnet particles be fixed in the sample stage. Then, spectral analysis is performed one by one under the electron probe. Finally, based on the major elements, the type of garnet is obtained through complex calculations of formulas. Due to the size of the electron probe sample stage, a small number of particles can be analyzed at one time, and samples need to be changed frequently. Each garnet needs to be focused and marked, which is inefficient and difficult to meet the needs of large-scale analysis.

[0004] Table 1 Optical identification characteristics of garnet Garnet color Other special Pyrope Red, purple, yellow-red Almandine Brown, dark red, purple Spessartine Yellow-orange, orange-red Andradite Yellow-green, emerald green, black Grossular Brownish yellow, yellow, yellowish green, green Ulvanoite green In addition, in the existing technology, for sample pre-treatment, it is necessary to manually stick the garnets into the double-sided tape one by one, which is extremely inefficient. Summary of the invention

[0005] The problem to be solved and the technical solution proposed by the present invention are to improve the existing technology, thereby providing a method for qualitative identification of a large number of garnets. The identification method of the present invention is accurate and efficient, and can obtain a large amount of heavy mineral geological information.

[0006] The above technical objectives of the present invention are achieved through the following technical solutions: According to one aspect of the present invention, the present invention provides a method for qualitatively identifying a large number of garnets, the method comprising the following steps: S1: washing the collected garnet particles with clean water and drying them at a temperature of 50-60°C; S2: Weigh 2g of Buehler epoxy resin and pour it into the mold, take 5g~10g of dried garnet and directly sprinkle it into the Buehler epoxy resin, stirring while pouring; S3: Vacuum the mold for 1-2 hours to ensure that there are no bubbles, and put it in a 40-50°C oven to solidify the resin. After the resin solidifies, polish the resin target with sandpaper, Al2O3 suspension, and polishing machine for 10 minutes until the inside of the sample particles are exposed; S4: Testing is performed using an automated mineral analysis software instrument, which includes the following steps: First, take a low-precision backscattered photo of the entire resin target, select the area to be scanned, and divide the scanning area into several small squares of 1200×1200μm; First, a high-precision backscatter image is taken inside a single small cube, and then the energy spectrum data is acquired point by point. Points are evenly placed inside the mineral particles, and points are densely placed at the mineral boundaries to obtain the best results. After the test is completed, the software automatically splices the backscattering data and energy spectrum data obtained from the test. The automatic mineral analysis software will compare the energy spectrum lines of unknown minerals and standard minerals to determine the specific type of minerals; S5: Offline data acquisition: The garnet species information, total particle number, and content of each type of garnet in the resin target can be exported offline in the test data; through the filter, minerals of a certain particle size can also be selected for statistics.

[0007] Preferably, in step S4, the resin target to be analyzed is subjected to carbon spraying treatment at room temperature for 30 minutes before being tested using the automatic mineral analysis software instrument.

[0008] Preferably, in step S4, during the test using the automatic mineral analysis software instrument, the acceleration voltage is 20 kV, the current is 10 nA, and the working distance is 20 mm; the dissociation mode is used in the test, and the X-ray counts at each point are 800. The pixel size is 4 μm, and the energy spectrum step length is 10 μm.

[0009] In summary, the present invention has the following beneficial effects: (1) The sample preparation process is fast. The target making process no longer requires manual gluing of garnets onto double-sided tape one by one. The garnet samples are fixed in the resin target directly by throwing, stirring, settling, and hollowing.

[0010] (2) The identification results are accurate and efficient. Through the energy spectrum scanning method, the species of minerals can be quickly identified. In a 3 cm diameter resin target, the total number of mineral identifications is no less than 2,000, and 2,000 valid data can be obtained (about 200 times the number of particles identified manually). A large amount of data can be obtained efficiently, improving the efficiency of mineral exploration.

[0011] (3) Eliminate the interference of human factors in the identification of heavy minerals, ensure data quality, and obtain a large amount of heavy mineral geological information. TIMA is an instrument that automatically scans and identifies minerals, mainly based on the brightness of the energy spectrum line and backscattering diagram. By comparing with the standard sample data under the same test conditions, it can accurately determine the type of mineral. The interference of human factors is completely eliminated during the data acquisition process. TIMA can provide the energy spectrum information of all heavy mineral particles, determine the specific species information of mineral particles, and more accurately reflect the characteristics of the sample. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The disclosure of the present invention will become easier to understand with reference to the accompanying drawings. It is easy for those skilled in the art to understand that these drawings are only used to illustrate the technical solution of the present invention and are not intended to limit the scope of protection of the present invention. In the drawings: Figure 1 This is a garnet resin target image obtained by processing in Example 1 of the present invention; Figure 2 This is a distribution characteristic diagram of ZMF garnet of sample A in Example 1 of the present invention; Figure 3 This is a characteristic spectrum diagram of ZMF magnesia-iron almandine sample A in Example 1 of the present invention; Figure 4 This is the target image of XK-01 orange garnet resin of sample B in Example 2 of the present invention; Figure 5 This is a distribution characteristic diagram of orange garnet of sample B XK-01 in Example 2 of the present invention; Figure 6 This is the energy spectrum characteristic diagram of orange-magnesium-aluminum-iron-aluminum garnet of sample B in Example 2 of the present invention. DETAILED DESCRIPTION

[0013] The following describes the embodiments of the present invention through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention.

[0014] It should be understood that the following specific embodiments are only used to illustrate the present invention and are not used to limit the scope of the present invention; it should also be understood that the terms used in the embodiments of the present invention are for describing specific specific embodiments rather than for limiting the scope of protection of the present invention; in the present specification and claims, unless otherwise clearly stated in the text, the singular forms "a", "an" and "the" include plural forms.

[0015] When the embodiment gives a numerical range, it should be understood that, unless otherwise specified in the present invention, both endpoints of each numerical range and the numerical value between the two endpoints can be selected. Unless otherwise defined, all technical and scientific terms used in the present invention have the same meaning as those generally understood by those skilled in the art. In addition to the specific methods, equipment, and materials used in the embodiments, according to the grasp of the prior art by those skilled in the art and the record of the present invention, any method, equipment, and material of the prior art similar or equivalent to the methods, equipment, and materials described in the embodiments of the present invention can also be used to realize the present invention.

[0016] Embodiment 1: The qualitative identification method of garnet in this embodiment is as follows: (1) The collected garnet (sample A ZMF, taken from the heavy sand sediment of the Zhimafang River system in Xinyi, Xuzhou) particles were first washed with clean water to remove most of the dust attached to the surface of the sample. The washed samples were dried at 55°C.

[0017] (2) Weigh 2g of Buehler epoxy resin and pour it into the mold. Take 6g of dried garnet and sprinkle it directly into the Buehler epoxy resin, stirring while pouring. Evacuate the mold for 2 hours to ensure that there are no bubbles. Put it in a 50℃ oven to solidify the resin. After the resin solidifies, use sandpaper, Al2O3 suspension, and a polishing machine to polish the resin target for 10 minutes and grind until the inside of the sample particles are exposed. The results can be seen Figure 1 .

[0018] (3) Testing using the TIMA instrument includes the following steps: The resin target to be analyzed is subjected to carbon spraying treatment.

[0019] First, take a low-precision backscattered photo of the entire resin target, select the area to be scanned, and divide the scanning area into several small squares of 1200×1200μm.

[0020] First, a high-precision backscattered image is taken inside a single small cube, and then the energy spectrum data is acquired point by point. Points are evenly placed inside the mineral particles and points are densely placed at the mineral boundaries to obtain the best results.

[0021] After the test is completed, the software automatically splices the backscatter data and energy spectrum data obtained from the test. The automatic mineral analysis software will compare the energy spectrum lines of unknown minerals and standard minerals to determine the specific type of mineral.

[0022] The TIMA instrument is mainly composed of a field emission scanning electron microscope, four energy spectrum probes and automatic analysis software. The data acquisition process is fully automatic and does not require human intervention. In the experiment, the accelerating voltage was 20kV, the current was 10nA, the working distance was 20mm, the current and BSE signal intensity were calibrated using the automatic program of the platinum Faraday cup, and the EDS signal was calibrated using the Mn standard. The dissociation mode was used in the test, the X-ray count at each point was 800, the pixel size was 4μm, and the energy spectrum step size was 10μm. The experiment used the dot mapping mode.

[0023] (4) Offline data acquisition: The garnet species information, total number of particles, and content of each type of garnet in the resin target can be exported offline in the test data; through the filter, minerals of a certain particle size can also be selected for statistics.

[0024] Finally, the number of garnet particles was 40, including 38 pyrope-iron almandine and 2 quartz, and the analysis time was 30 minutes. Figure 2 As shown, the energy spectrum characteristics of magnesia-iron almandine are as follows Figure 3 shown.

[0025] Embodiment 2: The qualitative identification method of garnet in the present embodiment is as follows: (1) The collected garnet (B sample XK-01 orange, taken from the heavy sand sediment of the Zhimafang River system in Xinyi, Xuzhou) particles were first washed with clean water to remove most of the dust attached to the sample surface. The washed samples were dried at 50°C.

[0026] (2) Weigh 2g of Buehler epoxy resin and pour it into the mold. Take 10g of dried garnet and sprinkle it directly into the Buehler epoxy resin, stirring while pouring. Evacuate the mold for 2 hours to ensure that there are no bubbles, put it in the oven to solidify the resin, and after the resin solidifies, use sandpaper, Al2O3 suspension, and polishing machine to polish the resin target for 1 minute and grind until the inside of the sample particles are exposed. The results can be seen Figure 4 .

[0027] (3) Testing using an automated mineral analysis software instrument includes the following steps: The resin target to be analyzed is subjected to carbon spraying treatment.

[0028] First, take a low-precision backscattered photo of the entire resin target, select the area to be scanned, and divide the scanning area into several small squares of 1200×1200μm.

[0029] First, a high-precision backscattered image is taken inside a single small cube, and then the energy spectrum data is acquired point by point. Points are evenly placed inside the mineral particles and points are densely placed at the mineral boundaries to obtain the best results.

[0030] After the test is completed, the software automatically splices the backscattering data and energy spectrum data obtained from the test. The automatic mineral analysis software will compare the energy spectrum lines of unknown minerals and standard minerals to determine the specific type of mineral.

[0031] The TIMA instrument is mainly composed of a field emission scanning electron microscope, four energy spectrum probes and automatic analysis software. The data acquisition process is fully automatic and does not require human intervention. In the experiment, the accelerating voltage was 20kV, the current was 10nA, the working distance was 20mm, the current and BSE signal intensity were calibrated using the automatic program of the platinum Faraday cup, and the EDS signal was calibrated using the Mn standard. The dissociation mode was used in the test, the X-ray count at each point was 800, the pixel size was 4μm, and the energy spectrum step size was 10μm. The experiment used the dot mapping mode.

[0032] (4) Offline data acquisition: The garnet species information, total number of particles, and content of each type of garnet in the resin target can be exported offline in the test data; through the filter, minerals of a certain particle size can also be selected for statistics.

[0033] Finally, after statistical analysis, the number of garnet particles was 180, including 92 ferroaluminum / sponselite garnets, 15 magnesia-ferroaluminum garnets, 56 grossular-ferroaluminum garnets, 7 grossular-ferroaluminum-(containing Mg) garnets, 6 grossular-ferroaluminum-(containing Mn) garnets, 2 tourmalines, and 2 quartzes. The analysis time was 30 minutes. Mineral distribution characteristics are as follows Figure 4 As shown, the energy spectrum characteristics of magnesia-iron almandine are as follows Figure 5 shown.

[0034] Comparative Example 1: The garnet qualitative identification method in this embodiment is as follows: (1) The collected garnet (sample A ZMF, taken from the heavy sand sediment of the Zhimafang River system in Xinyi, Xuzhou) particles were first washed with clean water to remove most of the dust attached to the surface of the sample. The washed samples were dried at 55°C.

[0035] (2) Weigh 2g of Buehler epoxy resin and pour it into the mold. Take 6g of dried garnet and sprinkle it directly into the Buehler epoxy resin, stirring while pouring. Evacuate the mold for 2h to ensure that there are no bubbles. Put it in a 50℃ oven to solidify the resin. After the resin solidifies, polish the resin target with sandpaper, Al2O3 suspension, and polishing machine for 10min and grind until the inside of the sample particles are exposed.

[0036] (3) Testing using the TIMA instrument includes the following steps: The resin target to be analyzed is subjected to carbon spraying treatment.

[0037] First, take a low-precision backscattered photo of the entire resin target, select the area to be scanned, and divide the scanning area into several small squares of 1000×1000μm.

[0038] First, a high-precision backscattered image is taken inside a single small cube, and then the energy spectrum data is acquired point by point. Points are evenly placed inside the mineral particles and points are densely placed at the mineral boundaries to obtain the best results.

[0039] After the test is completed, the software automatically splices the backscattering data and energy spectrum data obtained from the test. The automatic mineral analysis software will compare the energy spectrum lines of unknown minerals and standard minerals to determine the specific type of mineral.

[0040] The TIMA instrument is mainly composed of a field emission scanning electron microscope, four energy spectrum probes and automatic analysis software. The data acquisition process is fully automatic and does not require human intervention. In the experiment, the accelerating voltage was 25kV, the current was 9nA, the working distance was 15mm, the current and BSE signal intensity were calibrated using the automatic program of the platinum Faraday cup, and the EDS signal was calibrated using the Mn standard. The dissociation mode was used in the test, and the X-ray counts at each point were 1000. The pixel size was 3μm, and the energy spectrum step size was 9μm. The experiment used the dot mapping mode.

[0041] (4) Offline data acquisition: The garnet species information, total number of particles, and content of each type of garnet in the resin target can be exported offline in the test data; through the filter, minerals of a certain particle size can also be selected for statistics.

[0042] Finally, after statistical analysis, 40 garnet particles were found, including 18 pyrope-almandine garnets, and the rest were unknown minerals (unidentified). The analysis time was 4 hours.

[0043] Comparative Example 2: The garnet qualitative identification method in this example is as follows: (1) The collected garnet (sample A ZMF, taken from the heavy sand sediment of the Zhimafang River system in Xinyi, Xuzhou) particles were first washed with clean water to remove most of the dust attached to the surface of the sample. The washed samples were dried at 55°C.

[0044] (2) Weigh 2g of Buehler epoxy resin and pour it into the mold. Take 0.6g of dried garnet and sprinkle it directly into the Buehler epoxy resin, stirring while pouring. Evacuate the mold for 2h to ensure that there are no bubbles. Put it in a 50℃ oven to solidify the resin. After the resin solidifies, polish the resin target with sandpaper, Al2O3 suspension, and polishing machine for 10min and grind until the inside of the sample particles are exposed.

[0045] (3) Testing using the TIMA instrument includes the following steps: The resin target to be analyzed is subjected to carbon spraying treatment.

[0046] First, take a low-precision backscattered photo of the entire resin target, select the area to be scanned, and divide the scanning area into several small squares of 1000×1000μm.

[0047] First, a high-precision backscattered image is taken inside a single small cube, and then the energy spectrum data is acquired point by point. Points are evenly placed inside the mineral particles and points are densely placed at the mineral boundaries to obtain the best results.

[0048] After the test is completed, the software automatically splices the backscatter data and energy spectrum data obtained from the test. The automatic mineral analysis software will compare the energy spectrum lines of unknown minerals and standard minerals to determine the specific type of mineral.

[0049] The TIMA instrument is mainly composed of a field emission scanning electron microscope, four energy spectrum probes and automatic analysis software. The data acquisition process is fully automatic and does not require human intervention. In the experiment, the accelerating voltage was 25kV, the current was 9nA, the working distance was 15mm, the current and BSE signal intensity were calibrated using the automatic program of the platinum Faraday cup, and the EDS signal was calibrated using the Mn standard. The dissociation mode was used in the test, and the X-ray counts at each point were 1000. The pixel size was 3μm, and the energy spectrum step size was 9μm. The experiment used the dot mapping mode.

[0050] (4) Offline data acquisition: The garnet species information, total number of particles, and content of each type of garnet in the resin target can be exported offline in the test data; through the filter, minerals of a certain particle size can also be selected for statistics.

[0051] Finally, after statistical analysis, there were 11 garnet particles, including 8 pyrope-almandine and 3 almandine, and the analysis time was 30 minutes.

[0052] The technical means disclosed in the scheme of the present invention are not limited to the technical means disclosed in the above-mentioned implementation mode, but also include technical schemes composed of any combination of the above-mentioned technical features. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications are also regarded as the protection scope of the present invention.

Claims

1. A method for qualitative identification of a large number of garnets, characterized in that: The method comprises the following steps: S1: washing the collected garnet particles with clean water and drying them at a temperature of 50-60°C; S2: Weigh 2g of Buehler epoxy resin and pour it into the mold, take 5g~10g of dried garnet and directly sprinkle it into the Buehler epoxy resin, stirring while pouring; S3: Vacuum the mold for 1-2 hours to ensure that there are no bubbles, and put it in a 40-50°C oven to solidify the resin. After the resin solidifies, polish the resin target with sandpaper, Al2O3 suspension, and polishing machine for 10 minutes until the inside of the sample particles are exposed; S4: Testing is performed using an automated mineral analysis software instrument, which includes the following steps: First, take a low-precision backscattered photo of the entire resin target, select the area to be scanned, and divide the scanning area into several small squares of 1200×1200μm; First, a high-precision backscatter image is taken inside a single small cube, and then the energy spectrum data is acquired point by point. Points are evenly placed inside the mineral particles, and points are densely placed at the mineral boundaries to obtain the best results. After the test is completed, the software automatically splices the backscattering data and energy spectrum data obtained from the test. The automatic mineral analysis software will compare the energy spectrum lines of unknown minerals and standard minerals to determine the specific type of minerals; S5: Offline data acquisition: The garnet species information, total particle number, and content of each type of garnet in the resin target can be exported offline in the test data; through the filter, minerals of a certain particle size can also be selected for statistics.

2. The identification method according to claim 1, characterized in that: In step S4, the resin target to be analyzed is subjected to carbon spraying treatment for 30 minutes at room temperature before being tested using the automatic mineral analysis software instrument.

3. The identification method according to claim 1, characterized in that: In step S4, during the test using the automatic mineral analysis software instrument, the acceleration voltage is 20 kV, the current is 10 nA, and the working distance is 20 mm; the dissociation mode is used in the test, the X-ray count at each point is 800, the pixel size is 4 μm, and the energy spectrum step is 10 μm.

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