Phase classification method for coal combustion fly ash

Abstract

The invention provides a phase classification method for coal combustion fly ash, and relates to the technical field of coal combustion byproduct analysis. The phase classification method comprises the following steps: performing consolidation treatment on a coal combustion fly ash sample to obtain a to-be-analyzed target sample; carrying out element component collection on the plurality of particle micro-areas in the to-be-analyzed target sample based on scanning electron microscope energy spectrum analysis to obtain the contents of main control elements and target elements; and according to the contents of the main control element and the target element, performing phase classification on the plurality of particles contained in the coal combustion fly ash sample, and determining the phase category to which each particle belongs. According to the method, through consolidation sample preparation and scanning electron microscope energy spectrum analysis, non-destructive and multi-element micro-area analysis of the fly ash particles is achieved, phase classification is completed based on the element content, and the classification accuracy and the research foundation are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of coal combustion by-product analysis, and in particular to a phase classification method for coal combustion fly ash. Background Art

[0002] The resource utilization of coal combustion by-products is one of the important directions for high-value utilization of solid waste and metal recovery. During the coal combustion or gasification process, secondary products such as combustion fly ash, fly ash and gasification slag are usually rich in basic elements such as silicon, aluminum, iron, as well as rare elements such as gallium and germanium. These by-products have become a research hotspot in the fields of circular economy and green mining in recent years due to their complex elemental composition and potential recycling value. In particular, in the development of alternative sources of scarce resources such as gallium and germanium, coal by-products are considered to be a promising alternative resource. The study of their occurrence state, mineral composition and distribution characteristics has become the basis for promoting the efficient recovery and comprehensive utilization of resources.

[0003] Currently, research on the composition and microstructure of coal combustion by-products primarily relies on chemical analysis, X-ray diffraction (XRD), and qualitative microscopic analysis using scanning electron microscopy (SEM) coupled with energy dispersive spectroscopy (EDS). Chemical selective dissolution and analysis is used to determine the total amount of elements, XRD reveals phase composition by examining the crystalline structure, and SEM provides particle-level morphological observations and local compositional information. Furthermore, automated mineral analysis systems (such as MLA and AMICS), widely used in ore analysis, are also being increasingly introduced into fly ash research. These systems typically extract particle boundaries using backscattered image grayscale, combine energy spectrum information with a database for mineral identification, and automatically calculate microscopic parameters such as relative content and particle size distribution.

[0004] However, since the characteristics of coal by-products are significantly different from those of traditional ores, such as finer particle size, more dispersed element distribution, and more complex composition, the application of existing methods to this type of material has many limitations. Although the chemical selective dissolution method can quantify the total amount of elements, it cannot restore the existence state and spatial distribution of each component. It is also a destructive method and the samples cannot be reused. Although the X-ray diffraction method can determine the type of phase, it cannot give the quantitative ratio of each phase, and it is difficult to distinguish amorphous or non-standard structured materials. Although scanning electron microscopy qualitative analysis can observe microscopic morphology and perform local composition testing, it lacks systematic classification rules and cannot perform batch identification and quantitative analysis. Although the mineral automatic analysis system has powerful recognition and calculation capabilities, due to the lack of standard classification methods and feature databases suitable for coal ash materials, its application accuracy and efficiency in this type of sample are low.

[0005] In summary, the main difficulties currently faced in studying the phase composition of coal combustion byproducts include: first, the limited information dimension of traditional analytical methods, which cannot achieve simultaneous identification and quantification of components; second, they are highly destructive and have poor sample reusability; and third, existing automatic identification systems lack adaptive models, making it difficult to accurately separate and extract features from complex mixed-phase samples. Therefore, establishing a refined phase separation strategy and automatic identification method for fly ash samples remains a major technical bottleneck in this field.

[0006] In view of this, the present invention is proposed. Summary of the Invention

[0007] The present invention aims to provide a method for phase classification of coal combustion fly ash. This method, through consolidation sampling and scanning electron microscopy (SEM) energy dispersive spectrometry, enables non-destructive, multi-element microanalysis of fly ash particles. Phase classification is performed based on elemental content, improving classification accuracy and fundamental research.

[0008] In order to achieve the above-mentioned purpose of the present invention, the following technical solutions are adopted: The present application provides a method for phase classification of coal combustion fly ash, comprising: S1, preparing the target sample to be analyzed by consolidating the coal combustion fly ash sample; S2, based on scanning electron microscope energy spectrum analysis, collecting elemental composition of multiple particle micro-regions in the target sample to be analyzed to obtain the content of main control elements and target elements; S3, performing phase classification on the multiple particles contained in the coal combustion fly ash sample according to the contents of the main control element and the target element, and determining the phase category to which each particle belongs.

[0009] In some embodiments, the main control element includes at least one of C, Fe, S, O, Si, Al, Ca and Mg; and / or the target element includes at least one of As, Ge, Ga, Sb and Pb.

[0010] In some embodiments, the step S3 of performing phase classification on the plurality of particles contained in the coal combustion fly ash sample according to the contents of the main control element and the target element to determine the phase category to which each particle belongs includes: S31, determining the main control phases of iron, carbon, sulfur and silicon contained in the particles of the target sample to be analyzed according to the content of the main control elements; S32, determining the silicon, calcium, and aluminum main phases contained in the particles other than the iron, carbon, sulfur, and silicon main phases; S33, for the particles of the iron-carbon-sulfur-silicon main phase and the silicon-calcium-aluminum main phase, further determine the sub-type phases of the target elements contained therein.

[0011] In some embodiments, the step S31 of determining the main control phases of iron, carbon, sulfur, and silicon contained in the target sample particles to be analyzed according to the content of the main control elements includes: All particles in the target sample to be analyzed are classified according to the contents of Fe, C, S and Si in the main control elements to determine the iron, carbon, sulfur and silicon main control phases contained in the particles; wherein the iron, carbon, sulfur and silicon main control phases include carbonaceous phase, iron phase, iron sulfide phase and FeSiO phase.

[0012] In some embodiments, the step of classifying all particles in the target sample to be analyzed according to the content of Fe, C, S, and Si in the main control elements includes: If the main controlling element of the particle only contains C, then the main controlling phase of iron, carbon, sulfur and silicon is a carbonaceous phase; If the mass content of Fe in the main controlling element of the particle is not less than 70%, the main controlling phase of iron, carbon, sulfur and silicon is a ferrous phase; If the sum of the mass contents of Fe and S in the main control elements of the particle accounts for more than 99% of the main control elements, the iron-carbon-sulfur-silicon main control phase is an iron sulfide phase; If the sum of the mass contents of Fe, Si and O in the main controlling elements of the particles is greater than 99%, the iron-carbon-sulfur-silicon main controlling phase is FeSiO phase.

[0013] In some embodiments, the step S32 of determining the silicon-calcium-aluminum main phase contained in the particles other than the iron-carbon-sulfur-silicon main phase includes: S321, determining whether the sum of the contents of Si, Ca, Al, and O elements contained in the particles other than the iron-carbon-sulfur-silicon main phase is greater than 90%; S322: If yes, then calculate the element content ratio of the element based on the content of Si, Ca and Al in the particles other than the iron, carbon, sulfur and silicon main phases based on a normalization method; the element content ratio is the ratio of the mass content of Si, Ca or Al in the particles to the total mass content of Si, Ca and Al; S323, determining the silicon-calcium-aluminum main controlling phase according to the mass content of the Si, Ca and Al elements and the proportion of the element contents.

[0014] In some embodiments, the calculation method of the element content ratio is: ; Wherein, i represents any one of Si, Ca, and Al; A represents the element content ratio of the element; and W is the mass content of the element in the particles obtained by scanning electron microscope energy spectrum analysis.

[0015] In some embodiments, the calcium-silicon-aluminum main phase includes a Ca-Al-Si transition phase, a Ca-Si wollastonite phase, an aluminum oxide corundum phase, an aluminum silicate phase, a Ca-containing aluminum silicate phase, a quartz phase, and a calcium oxide phase; The step S323, determining the silicon-calcium-aluminum main phase according to the content of the Si, Ca and Al elements and the proportion of the element contents, includes: If W in the particles Si 、W Ca and W Al are between 20% and 50%, and A Si 、A Ca and A Al If both are 0.25, the main silicon-calcium-aluminum phase is a Ca-Al-Si transition phase; If the particles contain A Ca >0.25, and (A Ca +A Si )>0.75, the main silicon-calcium-aluminum phase is Ca-Si wollastonite phase; If W in the particles Al >45%, and A Al >0.75, the main phase of the silicon calcium aluminum is the aluminum oxide corundum phase; If W in the particles Al Between 30% and 40%, and 0.15<A Al <0.50, A Ca <0.05; then the main silicon calcium aluminum phase is aluminosilicate phase; If 0.05≤A Ca <0.25,0.30≤A Si <0.80,0.15≤A Al <0.60, the main silicon-calcium-aluminum phase is a Ca-aluminum silicate phase: If W in the particles Si ≥43%, and meet W Si >60% or A Si ≥0.85, the main phase of the silicon calcium aluminum is the quartz phase: If the particles (W Ca +W O )>80%,(W Al +W Si )<10%,A Ca >0.75, the main phase of the silicon-calcium-aluminum is the calcium oxide phase; Among them, W Si 、W Ca 、W Al and W ORespectively represent the mass contents of Si, Ca, Al and O in the particles obtained by scanning electron microscope energy spectrum analysis; A Si 、A Ca and A Al Respectively represent the proportion of the element content corresponding to Si, Ca and Al elements.

[0016] In some embodiments, the target element subtype phases include high As phase, low As phase, high Ge phase, low Ge phase, high Sb phase and low Sb phase; The method for determining the subclass difference of the target element includes: If 0%<W As ≤3%, then the target element sub-phase is a low As phase; If W in the particles As >3%, the target element sub-phase is a high As phase; If 0%<W Ge ≤1%, then the target element sub-phase is low Ge phase; If W in the particles Ge >1%, the target element sub-phase is a high Ge phase; If 0%<W Sb ≤1%, then the target element sub-phase is a low Sb phase; If W in the particles Sb >1%, the target element sub-phase is a high Sb phase.

[0017] In some embodiments, the step S3, after performing phase classification on the multiple particles contained in the coal combustion fly ash sample according to the contents of the main control element and the target element and determining the phase category to which each particle belongs, further comprises: S4, entering the mass content and energy spectrum of the main control element and the target element corresponding to each phase category determined into a mineral analysis system to form an identification database; S5, setting identification parameters in the mineral analysis system so that particles show distinguishable brightness differences in the image; wherein the identification parameters include at least one of magnification, image brightness, and image contrast; S6, using the identification database and the identification parameters, automatically identifying particles in the target sample to be analyzed by the mineral analysis system to obtain identification results of each phase category; S7, if there are unidentified particles in the automatic identification, and the proportion of the unidentified particles exceeds a preset proportion threshold, performing mass content analysis of the main control element and the target element on the unidentified particles to determine whether they can be classified into the existing phase category; S8, if it can be classified into the existing phase category, updating the mass content and energy spectrum of the main control element and the target element corresponding to the phase category in the identification database; S9. If the particle cannot be classified into the existing phase category, a new phase category is determined based on the mass content of the main control element and the target element of the unidentified particle, and the content and energy spectrum of the main control element and the target element of the new phase category are entered into the identification database.

[0018] The present application provides a phase classification method for coal combustion fly ash, which comprises: first, preparing a coal combustion fly ash sample into a target sample to be analyzed by epoxy resin consolidation; second, based on scanning electron microscope energy spectrum analysis, collecting elemental components of micro-areas of multiple particles in the target sample to obtain the contents of main control elements and target elements; finally, based on the contents of the above-mentioned main control elements and target elements, performing phase classification on multiple particles to determine the phase category to which they belong.

[0019] This method consolidates powdered coal combustion fly ash samples to transform them into target samples with stable structure and smooth surface, which facilitates subsequent high-resolution scanning electron microscope energy spectrum analysis, improves test repeatability and data reliability, and avoids the problem of particle movement or positioning difficulties in the measurement process of traditional bulk samples.

[0020] During the composition acquisition process, a scanning electron microscope combined with energy dispersive spectroscopy (EDS) analysis can accurately determine the contents of key control elements (such as Fe, Si, and Al) and target elements (such as Ge, As, and Sb) in micron-scale particle regions. This method can simultaneously obtain spatial distribution information for multiple elements. Compared to traditional chemical analysis methods, it offers the advantages of being non-destructive, providing high compositional resolution, and being suitable for micro-region identification.

[0021] By collecting mass content data for key control and target elements, phase classification of multiple particles can be performed to identify and differentiate the different microscopic components in coal combustion fly ash, providing foundational information for further analysis of the occurrence state, resource utilization potential, and microstructural characteristics of each phase. This phase classification method incorporates multi-element quantitative data, making the classification results more scientific and applicable, and avoiding the vague classification that relies solely on macroscopic characteristics or a single element.

[0022] Therefore, this method can complete the microscopic phase classification of multiple particles in coal combustion fly ash samples based on high spatial resolution energy spectrum data without destroying the overall structure of the sample, thereby improving the accuracy and systematicity of fly ash component analysis and providing a reliable basis for subsequent element occurrence research, resource utilization path formulation, and other work. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0024] Figure 1 Schematic diagram of the process of the phase classification method of coal combustion fly ash in the embodiment of the present application; Figure 2 The Si-Ca-Al multi-element main controlling element phase diagram of the phase classification method of coal combustion fly ash in the embodiment of the present application; Figure 3 This is the Si-Ca-Al multi-element main controlling element phase diagram in the embodiment of the present application (each point represents the data obtained from a measurement point); Figure 4 Schematic diagram of the Ca-Si-Al transition phase composition and energy spectrum characteristic diagram obtained by building a component library in the AMICS mineral automatic analysis system in the embodiment of the present application; Figure 5 This is a scanning electron microscope backscattered microscopic morphology image of fly ash particles identified by the mineral automatic analysis system software in the embodiment of the present application; Figure 6 This is a particle map of the As-containing CaSiO phase identified and extracted in the examples of this application. DETAILED DESCRIPTION

[0025] The embodiments of the present invention will be described in detail below with reference to the examples, but it will be understood by those skilled in the art that the following examples are merely illustrative of the present invention and should not be construed as limiting the scope of the invention. Where specific conditions are not specified in the examples, the methods were performed according to conventional conditions or the conditions recommended by the manufacturer. Where the manufacturers of the reagents or instruments are not specified, they are all commercially available conventional products.

[0026] refer to Figure 1 In an embodiment of the present application, a method for phase classification of coal combustion fly ash is provided, comprising: Step S1: preparing a target sample to be analyzed by consolidating a coal combustion fly ash sample.

[0027] The "coal combustion fly ash sample" described in the examples of the present application refers to a granular solid substance generated by coal during combustion and collected, which is a solid by-product discharged during the coal utilization process. The fly ash sample usually exists in the form of powder with a small particle size. It mainly comes from the combustion exhaust of coal-fired power plants, industrial boilers and other equipment, and is collected through a dust collector (such as an electrostatic precipitator, a bag filter). This type of sample generally contains common inorganic elements such as silicon, aluminum, iron, calcium, and magnesium, and may be doped with trace amounts of scattered elements or heavy metal elements such as germanium, arsenic, and antimony. The coal combustion fly ash sample has the characteristics of fine particles, complex composition, and diverse phases. It is the source of the original material for the object to be analyzed in the examples of the present application.

[0028] In this step, the original coal combustion fly ash sample is subjected to a consolidation treatment, which may include but is not limited to physical fixation and embedding treatment, so that it becomes a form suitable for subsequent microscopic analysis, namely, the "target sample to be analyzed."

[0029] The "consolidation treatment" refers to the process of converting powdered coal combustion fly ash samples into solid samples with certain structural strength and surface polishability, so as to facilitate subsequent micro-area testing operations such as scanning electron microscope energy spectrum analysis.

[0030] The consolidation treatment is not limited to the use of epoxy resin materials, and may also include but is not limited to the following methods: using ultraviolet light curing resin to quickly solidify the sample; using hot pressing to press the powder into a sample with a stable physical structure; using an organic embedding agent or a low-melting point inorganic flux to wrap the fly ash and cool it to solidify; using a polymer matrix material (such as acrylic resin, polyurethane, etc.) for consolidation molding.

[0031] Through the above-mentioned consolidation treatment, the original fly ash particles can maintain a stable position in space, preventing the particles from displacement, rolling or loss during microscopic analysis, and providing a good polishing interface to improve the subsequent imaging quality and the accuracy of energy spectrum acquisition.

[0032] In a preferred embodiment, the consolidation treatment method can be an epoxy resin consolidation method. Specifically, the fly ash sample is dispersed in alcohol, then mixed with a mixture of epoxy resin and a curing agent. The mixture is poured into a mold, degassed by vacuum or vibration, and then heat-cured. After cooling and forming, the sample is polished to obtain a target sample with a smooth surface.

[0033] In this step, epoxy resin and curing agent are usually mixed to embed the fly ash particles; after stirring to remove bubbles, the mixture is injected into the mold; after heating and curing, it is polished to form a smooth surface.

[0034] For example, the following steps may be included: (1) Take 0.1g~0.2g of sample and use solvent (such as alcohol) as the medium for dispersion; the sampling amount can be 0.11g, 0.12g, 0.13g, 0.15g, 0.16g, 0.18g, 0.19g, 0.20g, etc.

[0035] (2) Mix epoxy resin and curing agent in a ratio of (4-5):1 and pour the mixture into the mold. The ratio can be 4:1, 4.2:1, 4.5:1, 4.8:1, 5:1, etc.

[0036] (3) Stir the dispersed sample, then add the remaining mixed solution and stir until there are no bubbles.

[0037] (4) Tap the mold lightly to accelerate the sedimentation of the sample. After heating, repeated stirring, and continuous heating, cool the sample with clean water to solidify it into an epoxy resin ring target.

[0038] (5) After fine grinding and polishing, the target sample can be used for subsequent measurement and research.

[0039] Through the above steps, a solid target sample with a smooth surface, fixed particles, and not easy to move can be obtained, which can withstand subsequent high-resolution scanning electron microscopy analysis.

[0040] This step can ensure high sample stability and prevent fly ash particles from shifting during analysis; facilitate continuous, large-field-of-view, multi-particle analysis; and improve imaging and energy spectrum analysis accuracy.

[0041] Step S2: Based on scanning electron microscope energy spectrum analysis, elemental composition of multiple particle micro-regions in the target sample to be analyzed is collected to obtain the contents of main control elements and target elements.

[0042] In this step, a scanning electron microscope (SEM) combined with an energy dispersive spectrometer (EDS) is used to perform elemental analysis on the local microscopic areas of multiple particles in the sample to extract element content data.

[0043] In this embodiment, the “Scanning Electron Microscope Energy Dispersive Spectrometer Analysis” refers to a material micro-region composition analysis method that is performed using a scanning electron microscope (SEM) and an energy dispersive spectrometer (EDS).

[0044] A scanning electron microscope uses a high-energy electron beam to scan the surface of a sample, generating various signals (such as backscattered electrons, secondary electrons, X-rays, etc.) for observing the surface morphology and structure of the sample; while an energy spectrometer is used to receive the characteristic X-rays generated by the interaction between the electron beam and the sample, identify the elements contained in the sample based on the characteristics of the X-ray energy, and calculate their mass percentage or atomic percentage.

[0045] In this embodiment, scanning electron microscope energy spectrum analysis is used to perform elemental analysis on micro-regions of multiple particles in the coal combustion fly ash target sample, and obtain the mass content of the main control elements and target elements in the micro-regions.

[0046] The energy spectrum analysis is a non-destructive test suitable for fly ash target samples after consolidation. It can achieve high-throughput, quantitative, and multi-element simultaneous determination of multiple particles at the micron scale. The analysis results can be used for subsequent phase classification and occurrence state judgment.

[0047] According to the analysis requirements, the acceleration voltage, beam spot size, working distance and other parameters of the scanning electron microscope can be adjusted. The energy spectrum analysis area can be single point, line scanning or surface scanning. The obtained data can be directly output as a content table or energy spectrum map.

[0048] In some embodiments, the "primary controlling elements" refer to common elements that are widely present in coal combustion fly ash and have high mass content. They are used to characterize the basic composition characteristics of each particle and serve as the basic data source for phase classification. These primary controlling elements may include one or more of C (carbon), Fe (iron), S (sulfur), O (oxygen), Si (silicon), Al (aluminum), Ca (calcium), and Mg (magnesium). These elements typically constitute the primary inorganic mineral phase components in fly ash, and their content and combination play a decisive role in determining the phase classification of the particles.

[0049] In some embodiments, the "target element" described in this embodiment refers to a characteristic element that has a relatively low content in coal combustion fly ash but has resource recovery value or environmental monitoring significance, and its content can be used to assist in determining the occurrence state of the phase or to divide the sub-phases.

[0050] In specific embodiments, the target elements may include one or more of As (arsenic), Ge (germanium), Ga (gallium), Sb (antimony), and Pb (lead). These elements may be present in trace amounts in particles composed of different primary control elements. Analyzing their content can help further refine the phase category to which the particles belong.

[0051] Through this step, local chemical information can be obtained at the micron scale. Data acquisition is based on non-destructive testing, and multi-element simultaneous analysis is performed, which is highly efficient and rich in information dimensions.

[0052] Specifically, a scanning electron microscope can be used in conjunction with an energy spectrometer (such as JEOL, FEI). The collection points can be obtained through manual point selection or automatic scanning. The more particles there are, the stronger the statistical representativeness.

[0053] Step S3: performing phase classification on the multiple particles contained in the coal combustion fly ash sample according to the contents of the main control element and the target element, and determining the phase category to which each particle belongs.

[0054] In this step, the element mass content data of the multiple particles collected in step S2 is used to analyze which phase each particle belongs to.

[0055] This step provides distinguishable phase classification results, facilitates subsequent research on the occurrence patterns of target elements in each phase, and facilitates the identification of key phases in the comprehensive recovery of fly ash resources.

[0056] The above three steps provided in this embodiment constitute a basic process for phase identification at the microscopic level, which has high-precision identification and analysis capabilities without introducing subsequent automatic identification and database.

[0057] In some embodiments, the step S3 of performing phase classification on the plurality of particles contained in the coal combustion fly ash sample according to the contents of the main control element and the target element to determine the phase category to which each particle belongs includes: Step S31 : determining the main control phases of iron, carbon, sulfur and silicon contained in the particles of the target sample to be analyzed according to the content of the main control elements.

[0058] This step screens each particle in the sample and determines whether it belongs to a specific "Fe, C, S, and Si dominant phase" based on the concentrations of the dominant elements Fe, C, S, and Si. This is typically determined by mass percentage using element ratios or additive logic.

[0059] Through this step, a part of the particles can be screened out and determined to belong to several basic mineral phases mainly composed of Fe, C, S, and Si (collectively referred to as "iron-carbon-sulfur-silicon main controlling phases").

[0060] The classification basis of this step is clear; typical components with a large proportion can be quickly identified; and clear boundaries are provided for further analysis of more complex components.

[0061] In some embodiments, the step S31 of determining the main control phases of iron, carbon, sulfur, and silicon contained in the target sample particles to be analyzed according to the content of the main control elements includes: Step S311: Classify all particles in the target sample to be analyzed according to the content of Fe, C, S and Si in the main control elements to determine the iron, carbon, sulfur and silicon main control phases contained in the particles; wherein the iron, carbon, sulfur and silicon main control phases include carbonaceous phase, iron phase, iron sulfide phase and FeSiO phase.

[0062] The "all particles in the target sample to be analyzed" mentioned above refers to all particles to be processed after S1 consolidation and S2 energy spectrum analysis. Phase determination is performed using only the content data of the four key control elements (Fe, C, S, and Si). Other key control elements, such as Ca and Al, are not considered in this step.

[0063] The above-mentioned “determining the main controlling phases of iron, carbon, sulfur and silicon contained in the particles” refers to classifying the particles into one of the following four phases based on the proportion characteristics of the above four elements.

[0064] Specifically including: "A: carbonaceous phase, B: ferrous phase, C: iron sulfide phase and D: FeSiO phase": these are the four phase types allowed to be identified in this step.

[0065] The specific judgment process can be as follows: (1) traverse each particle; (2) obtain the mass percentage of the four elements Fe, C, S, and Si in the particle; (3) apply the set rules (such as whether it contains only C, whether the Fe ratio is ≥70%, whether Fe+S is ≥99%, etc.); (4) classify the particles into the corresponding phases (carbonaceous phase, iron phase, iron sulfide phase, FeSiO phase).

[0066] The result of this step can be to identify some particles in the fly ash sample as: containing only carbon → carbonaceous phase; high iron content → ferrous phase; iron-sulfur composite → iron sulfide phase; mainly iron, silicon and oxygen → FeSiO phase.

[0067] The above phases are the main components in fly ash and are also the most representative basic categories in the overall phase analysis.

[0068] This step has clear classification logic and quantifiable judgment criteria, which facilitates batch processing and automatic identification. It can complete efficient initial screening by relying on only a small amount of components in the main control element, which is beneficial to improving the overall phase classification efficiency and providing a stable foundation for the subsequent calling and training of the image recognition system.

[0069] In some embodiments, the step of classifying all particles in the target sample to be analyzed according to the content of Fe, C, S, and Si in the main control elements includes: (1) If the main controlling element of the particle contains only C, then the iron-carbon-sulfur-silicon main controlling phase is a carbonaceous phase. Screen particles that contain only carbon (C) in the main controlling element and do not contain other specified main controlling elements; if C is the only main controlling element, it means that the phase of this type of particle is mainly composed of carbon; this particle is classified as a "carbonaceous phase."

[0070] (2) If the mass content of Fe in the particle is not less than 70%, the primary controlling phase of iron, carbon, sulfur, and silicon is a ferruginous phase. Analyze the mass content of Fe in the particle; if the Fe content is extremely high (≥70%), it indicates that the phase is dominated by iron and is classified as a "ferruginous phase." A high Fe content provides a stable basis for judgment and is suitable for typical iron-rich particles.

[0071] (3) If the sum of the mass contents of Fe and S in the main controlling elements of the particle accounts for more than 99% of the main controlling elements, then the iron-carbon-sulfur-silicon main controlling phase is an iron sulfide phase. Calculate the proportion of the total mass content of Fe and S in the main controlling elements; if the sum of the two exceeds 99%, it means that the particle is composed of iron and sulfur, which meets the basic composition of iron sulfide; it is determined to be an "iron sulfide phase."

[0072] (4) If the sum of the mass contents of Fe, Si, and O in the particle's primary controlling elements exceeds 99%, the primary iron-carbon-sulfur-silicon phase is the FeSiO phase. The sum of the Fe, Si, and O contents; if the three-element composition exceeds 99%, it indicates a typical Fe-Si-O ternary oxide or compound structure, and the particle is classified as the "FeSiO phase." This ternary determination mechanism improves the accuracy of identifying particles with complex structures.

[0073] This step provides a clear classification method for four typical phases, based on the mass percentage threshold of the dominant element in the particle. All judgment criteria are quantitative, facilitating automated processing and batch identification, laying the foundation for more detailed phase classification later.

[0074] Step S32: Determine the silicon, calcium, and aluminum primary phases contained in particles other than the iron, carbon, sulfur, and silicon primary phases. After excluding particles with iron, carbon, sulfur, and silicon primary phases, the remaining particles are further evaluated to determine whether they meet the structural composition characteristics dominated by Si, Ca, and Al. A second level of classification is then performed on the remaining particles to select phases dominated by Si, Ca, and Al.

[0075] This step avoids the confusion of particles from different master control systems; normalization processing can be used to eliminate the interference of absolute content differences in samples; and the classification standard can be judged through numerical logic and is easy to implement.

[0076] In some embodiments, the step S32 of determining the silicon-calcium-aluminum main phase contained in the particles other than the iron-carbon-sulfur-silicon main phase includes: Step S321 , determining whether the sum of the contents of Si, Ca, Al and O elements contained in the particles other than the iron-carbon-sulfur-silicon main phase is greater than 90%.

[0077] In this step, particles that do not belong to the main controlling phases of iron, carbon, sulfur and silicon are first screened out, and then the total mass content of the four elements Si, Ca, Al and O in these particles is calculated.

[0078] Specifically, the elemental content data for each particle can be read and summed up one by one. If the combined mass content of these four elements exceeds 90%, the particle is likely to be a "Si-Ca-A" dominant phase. Using a high elemental sum as a prerequisite for screening can effectively eliminate irrelevant particles and improve classification accuracy.

[0079] Step S322: If yes, then based on the normalization method, the element content ratio of the element is calculated according to the content of Si, Ca and Al elements in the particles other than the iron-carbon-sulfur-silicon main phase; the element content ratio is the ratio of the mass content of Si, Ca or Al elements in the particles to the total mass content of Si, Ca and Al elements.

[0080] For particles that meet S321, the three elements Si, Ca, and Al are normalized to obtain the relative proportion of each element in the three.

[0081] The above-mentioned "normalization method" is a method of converting data of different scales, different units or different absolute values into a unified scale range (usually 0~1), so that the data are comparable and convenient for subsequent analysis or classification judgment.

[0082] The above-mentioned element content ratio refers to the ratio of the mass content of any one of the three elements Si, Ca and Al in a particle to the total mass of the three elements. Furthermore, the calculation method of the element content ratio is: ; Wherein, i represents any one of Si, Ca, and Al; A represents the element content ratio of the element; W is the mass content of the element in the particles obtained by scanning electron microscope energy spectrum analysis.

[0083] For example, the mass contents of the three elements in the particles are =30%, =40%, =10%, then we have the following: (1) =30 / (30+40+10)=0.429; (2) =40 / (30+40+10)=0.5; (3) =10 / (30+40+10)=0.125; these values are the proportions of element contents, reflecting the composition ratio between the three elements, which are used to identify which silicon-calcium-aluminum main phase the particles belong to.

[0084] The reason for using the percentage of element content is that since there are many types of elements in fly ash particles, the absolute content is easily affected by particle size, density, etc., while the percentage as a relative value is more stable and comparable, which facilitates the establishment of unified classification rules and phase identification models.

[0085] Step S323: Determine the silicon-calcium-aluminum main phase according to the mass content of the Si, Ca and Al elements and the proportion of the element content.

[0086] In this step, the mass content and normalized percentage of the three elements obtained in S322 are used as dual criteria to determine the type of "Si-Ca-Al-Dominant Phase" to which the particle belongs. The particle is then classified into a specific Si-Ca-Al-Dominant Phase category. This dual-metric cross-judgment of "mass content + percentage" improves classification accuracy and stability, supporting subsequent automatic identification.

[0087] In some embodiments, the calcium-silicon-aluminum-dominant phase includes a Ca-Al-Si transition phase, a Ca-Si wollastonite phase, an aluminum oxide corundum phase, an aluminum silicate phase, a Ca-containing aluminum silicate phase, a quartz phase, and a calcium oxide phase.

[0088] The step S323, determining the silicon-calcium-aluminum main phase according to the content of the Si, Ca and Al elements and the proportion of the element contents, includes: (1) If W in the particle Si 、W Ca and W Al are between 20% and 50%, and A Si 、A Ca and A Al If both are 0.25, the main silicon-calcium-aluminum phase is a Ca-Al-Si transition phase; (2) If the particle A Ca >0.25, and (A Ca +A Si )>0.75, the main silicon-calcium-aluminum phase is Ca-Si wollastonite phase; (3) If W in the particles Al >45%, and A Al >0.75, the main phase of the silicon calcium aluminum is the aluminum oxide corundum phase; (4) If W in the particle Al Between 30% and 40%, and 0.15<A Al <0.50, A Ca <0.05; then the main silicon calcium aluminum phase is aluminosilicate phase; (5) If 0.05≤A in the particle Ca <0.25,0.30≤A Si <0.80,0.15≤A Al <0.60, the main silicon-calcium-aluminum phase is a Ca-aluminum silicate phase: (6) If W in the particle Si ≥43%, and meet W Si >60% or A Si≥0.85, the main phase of the silicon calcium aluminum is the quartz phase: (7) If the particle (W Ca +W O )>80%,(W Al +W Si )<10%,A Ca >0.75, the main phase of the silicon-calcium-aluminum is the calcium oxide phase; Among them, W Si 、W Ca 、W Al and W O Respectively represent the mass contents of Si, Ca, Al and O in the particles obtained by scanning electron microscope energy spectrum analysis; A Si 、A Ca and A Al Respectively represent the proportion of the element content corresponding to Si, Ca and Al elements.

[0089] For details on the above evaluation criteria, please refer to Figure 2 The Si-Ca-Al multi-element main controlling element phase diagram is shown.

[0090] Step S33: for the particles having the iron-carbon-sulfur-silicon main phase and the silicon-calcium-aluminum main phase, further determining the sub-type phases of the target elements contained therein.

[0091] In this step, the target element (such as As, Ge, Sb, etc.) content levels of the particles classified in the first two steps are further analyzed to determine whether they have characteristic sub-class attributes, thereby generating finer-grained phase identification results, including the distinction of the occurrence state of the target elements, to facilitate subsequent recycling or environmental judgment.

[0092] Furthermore, the target element sub-phases include high As phase, low As phase, high Ge phase, low Ge phase, high Sb phase and low Sb phase; The method for determining the subclass difference of the target element includes: (1) If 0% in the particle is less than W As ≤3%, then the target element sub-phase is a low As phase; (2) If W in the particle As >3%, the target element sub-phase is a high As phase; (3) If 0% in the particle is less than W Ge ≤1%, then the target element sub-phase is low Ge phase; (4) If W in the particle Ge >1%, the target element sub-phase is a high Ge phase; (5) If 0% in the particle is less than W Sb≤1%, then the target element sub-phase is a low Sb phase; (6) If W in the particle Sb >1%, the target element sub-phase is a high Sb phase.

[0093] In some embodiments, the step S3, after performing phase classification on the multiple particles contained in the coal combustion fly ash sample according to the contents of the main control element and the target element and determining the phase category to which each particle belongs, further comprises: Step S4: Enter the mass contents and energy spectra of the main control elements and target elements corresponding to the determined phase categories into a mineral analysis system to form an identification database.

[0094] In this step, the mass content information of the main control elements and target elements of each type of identified phase, as well as the energy spectrum information of this type of particles, are uniformly entered into the mineral analysis system to form an identification database that can be called.

[0095] The above input content can include the characteristic element content range of each phase and the corresponding energy spectrum (element distribution map), so as to establish a standardized phase identification template and provide a comparison basis for subsequent automatic particle identification.

[0096] The above-mentioned "mineral analysis system" in this embodiment refers to an automated analysis platform that integrates image acquisition, component analysis, image recognition, data processing and result output, and is commonly used to identify and count the mineral composition, element distribution and phase characteristics of various particles in solid materials.

[0097] A mineral analysis system typically includes the following core modules: an image acquisition module, which uses a scanning electron microscope (SEM) to capture the sample's surface image and particle morphology; an energy spectrum analysis module (EDX / EDS), which performs energy spectrum detection on the particle area to collect its elemental composition and content; an identification and comparison module, in which the system compares the collected energy spectrum data with a built-in identification database (containing the corresponding element content and energy spectrum diagram) to identify the phase; an image processing and classification module, which identifies and classifies particle outlines based on pre-set identification parameters (such as brightness, contrast, and magnification); and a data statistics and output module, which calculates the number, proportion, and particle size distribution of each phase of particles and generates an analysis report. Specifically, a database management system can be used to classify and store data by phase label, and energy spectrum diagrams can be managed by pairing image files (such as TIFF) with data records.

[0098] The above-mentioned mineral analysis system may include but is not limited to the following systems: (1) QEMSCAN (Quantitative Evaluation of Minerals by Scanning Electron Microscopy); (2) MLA (Mineral Liberation Analyzer); (3) TIMA (TESCAN Integrated Mineral Analyzer); (4) AMICS (Automated Mineralogy Inc. System).

[0099] Step S5, setting identification parameters in the mineral analysis system so that particles show distinguishable brightness differences in the image; wherein the identification parameters include at least one of magnification, image brightness, and image contrast; In order to facilitate the automatic recognition system to process the image, it is necessary to set the image acquisition parameters in advance, such as magnification, brightness, contrast, etc.

[0100] In this step, image parameters can be set so that particles of different physical phases have sufficient grayscale or brightness differences in the microscopic image, thereby facilitating automatic image segmentation and particle recognition, and improving recognition accuracy and resolution.

[0101] Specifically, settings can be adjusted in the SEM or image processing software, where parameters can be optimized according to the sample type.

[0102] Step S6: using the identification database and the identification parameters, the mineral analysis system automatically identifies the particles in the target sample to be analyzed to obtain identification results of various phase categories.

[0103] In this step, the system automatically identifies and classifies particles in the new sample using the aforementioned database and identification parameters. Specifically, this process involves comparing the master / target element data collected from the particles with existing information in the database and determining the phase to which the particles belong.

[0104] It can be done with the help of image recognition + spectral comparison algorithm; specific technologies may include cluster analysis, spectrum matching, etc., so as to achieve high-throughput and high-efficiency recognition and further reduce the cost of manual intervention.

[0105] Step S7: If there are unidentified particles in the automatic identification, and the proportion of the unidentified particles exceeds the preset proportion threshold, the mass content of the main control element and the target element is analyzed for the unidentified particles to determine whether they can be classified into the existing phase category.

[0106] If the system finds that some particles do not match the physical phase classification in the database, and the proportion exceeds a preset threshold, further analysis is triggered manually or automatically. These particles are re-analyzed to collect their main control / target element content and determine whether they belong to existing classifications, thereby preventing missed detections or misclassifications and improving the coverage and robustness of the recognition system.

[0107] The threshold setting can be adjusted flexibly (e.g., 5%, 10%); re-analysis can be completed by an automatic system or manual review. In this embodiment, the preset ratio threshold can be set to 5%.

[0108] Step S8: If it can be classified into the existing phase category, the mass content and energy spectrum of the main control element and the target element corresponding to the phase category in the identification database are updated.

[0109] If it is confirmed that the unidentified particles can be classified into an existing phase category, the database information for that category is updated. Specifically, the element content range corresponding to the category can be supplemented or revised, and new energy spectrum samples can be added. This step allows for continuous adaptive optimization of the database and improves subsequent recognition accuracy.

[0110] Step S9: If the particle cannot be classified into the existing phase category, a new phase category is determined based on the mass content of the main control element and the target element of the unidentified particle, and the content and energy spectrum of the main control element and the target element of the new phase category are entered into the identification database.

[0111] If particles cannot be classified into existing categories, a new phase category is created and added to the database. The characteristics of this new category can be determined based on the content of the master / target element. The representative performance spectrum is saved and assigned a new label.

[0112] This step expands the recognition system's capabilities to support the discovery and classification of unknown phases. New categories can be numbered (e.g., "Phase X1"), and algorithm training can be enhanced over time as the number of recognized samples accumulates.

[0113] In the above method, a closed-loop phase recognition system is constructed, which includes database establishment, image parameter setting, automatic recognition, result backtracking and dynamic update. The core of the system is to achieve automation, sustainable optimization and self-learning recognition, and it has strong engineering practicality and scalability.

[0114] The present invention is further described below by way of specific examples. However, it should be understood that these examples are merely provided for more detailed description and are not to be construed as limiting the present invention in any form.

[0115] Example In this example, germanium-rich fly ash, generated after the combustion of a germanium-containing lignite, was used as the coal combustion fly ash sample. The composition of the fly ash was quantified. In particular, the occurrence of germanium and arsenic, two elements relevant to the germanium extraction process, required quantitative analysis and micromorphological analysis. Therefore, the following detailed methods were used to classify, automatically identify, and quantitatively measure the various phases in the fly ash.

[0116] Experimental methods and results: (1) The fly ash powder sample was solidified with epoxy resin and then formed into a circular target sample through a grinding and polishing process as the target sample to be analyzed.

[0117] (2) Under the scanning electron microscope (SEM), the in-situ micro-region composition of the component particles in the sample was collected. A total of 200 particles were randomly collected, and the composition of each particle was recorded according to Table 1.

[0118] Table 1. In-situ micro-area composition analysis results of fly ash particles (%)

[0119] (3) Determination of the differences between simple main control elements: According to the composition analysis results in Table 1, the sample contains carbon (C content 100%); if the Fe content is above 70% and there is no S, it can be determined that there is a ferrous phase; if there is mainly Fe and S (Fe+S content>97%), it can be determined to be an iron sulfide phase; if there is mainly Fe and Si, it can be determined to be an iron silicate phase (Table 2).

[0120] Table 2. Composition of some iron sulfides, iron phases, and some FeSiO (%)

[0121] (4) Determination of the phase difference of Si, Ca, and Al: The phase difference of the remaining particles with Si, Ca, and Al as the main controlling elements is determined by calculating the relative proportion A value of Si, Ca, and Al, combining the W values of Si, Ca, Al, and O and using the three-phase diagram (refer to Figure 3 ), the related particles fell into the alumina phase, Ca-Al-Si phase, calcium oxide phase, Ca-Si phase, Ca-containing aluminosilicate phase, aluminosilicate phase and quartz phase respectively.

[0122] (5) According to the needs of subsequent recycling and utilization, the content of Ge and As in the fly ash needs to be paid attention to. It can be seen that Ge and As mainly appear in the Ca-Al-Si phase, Ca-Si phase and CaO phase (Table 3), because they are further divided into the Ca-Al-Si phase containing Ge, the Ca-Al-Si phase containing GeAs, the Ca-Si phase containing As, the Ca-Si phase containing GeAs and the CaO phase containing As.

[0123] Table 3. Composition of some phases containing Ge and As (%)

[0124] (6) Using AMICS mineral automatic analysis software, the composition and spectrum of each phase are entered to form an identification database (reference Figure 4 ).

[0125] (7) In the automatic identification setting system of AMICS mineral automatic analysis software, the fly ash particles can be effectively distinguished by adjusting the magnification, brightness and contrast (refer to Figure 5 ).

[0126] (8) The automatic recognition results are shown in Table 4. After one recognition, the unrecognizable content is only , so this classification meets the research needs.

[0127] Table 4. Measurement results of relative content of each identification item / %

[0128] (9) The particle images of each phase can be directly classified and extracted by mineral automatic analysis software (refer to Figure 6 ), so the particle diameter and two-dimensional cross-sectional area can be directly measured, or microscopic morphology research can be carried out.

[0129] Comparative Example 1 In this comparative example, fly ash samples were collected from an economizer of a power plant in Guizhou Province, China as coal combustion fly ash samples, and specific classification and identification tests of various phases in the fly ash were performed.

[0130] 1. Experimental methods: (1) Sample collection and processing: Fly ash samples were collected from the economizer of a power plant in Guizhou Province, China, and sieved according to different particle sizes.

[0131] (2) Chemical analysis: X-ray fluorescence spectrometry (XRF) was used to determine the main element composition of fly ash; inductively coupled plasma mass spectrometry (ICP-MS) was used to determine the rare earth content in fly ash.

[0132] (3) Chemical selective sequential dissolution method: chemical species are divided into five types through four-step dissolution: ion exchange form, acid soluble form, metal oxide form, organic or sulfide form and silicate-aluminosilicate form.

[0133] (4) Scanning electron microscopy-energy dispersive spectrophotometry (SEM-EDS) analysis: used to study the morphology and microstructure of fly ash and determine the distribution of some elements.

[0134] 2. Experimental results: Through chemical selective dissolution and scanning electron microscopy-energy dispersive spectroscopy (SEM-EDS) analysis, the phase classification results of rare earth elements in fly ash were obtained: Main occurrence form: Rare earth elements are mainly found in the form of silicate-aluminosilicate (accounting for 65.22%), which indicates that REY is more tightly bound to aluminum and phosphorus, and relatively weakly bound to silicon.

[0135] Other occurrence forms: Organic or sulfide forms: 12.12%; this may be related to unburned carbon and sulfide minerals. Acid-soluble forms: 10.21%; this may be related to the combustion products of carbonate minerals (such as calcium oxide and magnesium oxide). Metal oxide forms: 7.11%; although the total content of iron, titanium, and manganese exceeds 15%, only a small amount of REY exists in the form of metal oxides. Ion-exchange forms: 5.35%; this indicates that some REY exists in an ionic state and may be easily released in inorganic salt solutions.

[0136] 3. Analysis: (1) As can be seen, the method used in Comparative Example 1 mainly classifies the occurrence forms of REY into five categories through chemical selective sequential extraction method (SCEP) and SEM-EDS analysis. This method focuses on chemical extraction and macroscopic analysis. Although it can provide classification results with a certain degree of accuracy, it may not be accurate enough in terms of particle classification and element distribution details at the microscopic level.

[0137] (2) The focus is mainly on the occurrence forms of rare earth elements (REY), with less involvement in the classification of other elements and phases.

[0138] Comparative Example 2 In this comparative example, high-alumina fly ash (HAFA) was used as the fly ash sample from coal combustion, and specific classification and identification tests of various phases in the fly ash were performed.

[0139] 1. Experimental methods: (1) Sample collection and processing: Samples were collected from power plants in Inner Mongolia and Shanxi, China, and separated into magnetic particles, glass phase, and mullite + corundum + quartz (MCQ) using magnetic separation and acid-base combined methods.

[0140] (2) Chemical analysis: X-ray fluorescence spectrometry (XRF) was used to determine the contents of oxides of major elements in the whole sample, magnetic particles, and MCQ; inductively coupled plasma optical emission spectrometry (ICP-OES) was used to determine the content of lithium.

[0141] (3) Time-of-flight secondary ion mass spectrometry (TOF-SIMS) analysis: used to observe the distribution of lithium in the whole sample, magnetic particles and MCQ.

[0142] (4) Solid-state nuclear magnetic resonance (NMR) analysis: 29Si solid-state magic angle spinning nuclear magnetic resonance (MAS NMR) technology was used to study the coordination structure of silicon in HAFA.

[0143] (5) Molecular simulation: The generalized gradient approximation (GGA) method was used to optimize the model compounds and calculate the energy difference between the reaction of lithium oxide and four model compounds in the glass phase.

[0144] 2. Experimental results: In Comparative Example 2, the phase classification results of lithium (Li) in high-alumina fly ash (HAFA) were obtained through acid-base combined separation and chemical analysis: (1) Main occurrence phase: Glass phase: 79%-94% of lithium exists in the glass phase. This phase is mainly composed of amorphous aluminum silicate and is the main occurrence form of lithium.

[0145] (2) Other existing phases: Mullite + corundum + quartz (MCQ) phase: 5%-16% of lithium exists in this phase.

[0146] Magnetic particle phase: Less than 5% lithium exists in the magnetic particles.

[0147] 3. Analysis: (1) Comparative Example 2: HAFA was separated into magnetic particles, a glassy phase, and an MCQ phase primarily through an acid-base combined method, and the distribution of lithium in each phase was determined through chemical analysis. This method focuses on macroscopic phase separation and chemical analysis, but has limited ability to analyze the classification of microscopic particles and the details of element distribution.

[0148] (2) The focus is mainly on the distribution of lithium in different phases, with less attention paid to the classification of other elements and phases.

[0149] In summary, the phase classification method provided in the examples of the present application shows significant beneficial effects in the phase classification of coal combustion fly ash compared with Comparative Examples 1 and 2.

[0150] Compared with the chemical extraction method in Comparative Example 1 that focuses on the occurrence form of rare earth elements, the phase classification method provided in the embodiment of the present application realizes non-destructive, multi-element micro-analysis of fly ash particles through consolidation sampling and scanning electron microscope energy spectrum analysis. It can not only accurately obtain the element content of particles at the micron scale, but also complete phase classification based on multi-element quantitative data. The classification accuracy is higher and various phases in fly ash can be comprehensively analyzed.

[0151] While Comparative Example 2 investigated the distribution of lithium in high-alumina fly ash, it primarily relied on combined acid-base separation and chemical analysis, limiting its ability to classify microscopic particles and analyze detailed element distribution. The phase classification method provided in the examples of this application further refines the phase categories to which particles belong. Its automated identification and database application enable high-throughput, high-efficiency phase identification, reducing manual intervention costs while optimizing identification accuracy through dynamic database updates.

[0152] Therefore, the method provided in the embodiment is not only superior to Comparative Example 1 and Comparative Example 2 in classification accuracy and comprehensive analysis, but also shows significant advantages in degree of automation and scope of application, and can provide more accurate and efficient basic data support for resource utilization, environmental monitoring and material science research of coal combustion fly ash.

[0153] The phase classification method provided in the examples of the present application is innovative and practical in the field of phase classification of coal combustion fly ash, making it stand out in comparison with Comparative Examples 1 and 2. Comparative Example 1 adopts a sequential chemical extraction procedure and scanning electron microscope-energy spectrum analysis. Although it can classify the occurrence forms of rare earth elements, its method focuses on macroscopic analysis and has limited classification accuracy for microscopic particles. Comparative Example 2 studies the distribution of lithium through acid-base combined separation and chemical analysis, and also lacks in-depth analysis of the microstructure. The phase classification method provided in the examples of the present application realizes multi-element micro-area analysis of fly ash particles at the micron scale through consolidation sample preparation and scanning electron microscope energy spectrum analysis, which can accurately obtain element content and complete phase classification.

[0154] Furthermore, the phase classification method provided in the examples of this application also incorporates automated identification and database applications, enabling high-throughput, high-efficiency phase identification, reducing manual intervention costs, and optimizing identification accuracy through dynamic database updates. These features not only improve classification accuracy and efficiency but also provide more comprehensive and in-depth data support for resource utilization and environmental monitoring of coal combustion fly ash, demonstrating the significant advancement and broad application prospects of the phase classification method provided in the examples of this application in this field.

[0155] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for phase classification of coal combustion fly ash, characterized in that: include: S1, preparing the target sample to be analyzed by consolidating the coal combustion fly ash sample; S2, based on scanning electron microscope energy spectrum analysis, collecting elemental composition of multiple particle micro-regions in the target sample to be analyzed to obtain the content of main control elements and target elements; S3, performing phase classification on the multiple particles contained in the coal combustion fly ash sample according to the contents of the main control element and the target element, and determining the phase category to which each particle belongs.

2. The method for phase classification of coal combustion fly ash according to claim 1, characterized in that: The main control element includes at least one of C, Fe, S, O, Si, Al, Ca and Mg; and / or, The target element includes at least one of As, Ge, Ga, Sb and Pb.

3. The method for phase classification of coal combustion fly ash according to claim 1, characterized in that: The step S3, performing phase classification on the multiple particles contained in the coal combustion fly ash sample according to the contents of the main control element and the target element to determine the phase category to which each particle belongs, includes: S31, determining the main control phases of iron, carbon, sulfur and silicon contained in the particles of the target sample to be analyzed according to the content of the main control elements; S32, determining the silicon, calcium, and aluminum main phases contained in the particles other than the iron, carbon, sulfur, and silicon main phases; S33, for the particles of the iron-carbon-sulfur-silicon main phase and the silicon-calcium-aluminum main phase, further determine the sub-type phases of the target elements contained therein.

4. The method for phase classification of coal combustion fly ash according to claim 3, characterized in that: The step S31, determining the main control phases of iron, carbon, sulfur and silicon contained in the particles of the target sample to be analyzed according to the content of the main control elements, includes: All particles in the target sample to be analyzed are classified according to the contents of Fe, C, S and Si in the main control elements to determine the iron, carbon, sulfur and silicon main control phases contained in the particles; wherein the iron, carbon, sulfur and silicon main control phases include carbonaceous phase, iron phase, iron sulfide phase and FeSiO phase.

5. The method for phase classification of coal combustion fly ash according to claim 4, characterized in that: The step of classifying all particles in the target sample to be analyzed according to the contents of Fe, C, S and Si in the main control elements includes: If the main controlling element of the particle only contains C, then the main controlling phase of iron, carbon, sulfur and silicon is a carbonaceous phase; If the mass content of Fe in the main controlling element of the particle is not less than 70%, the main controlling phase of iron, carbon, sulfur and silicon is a ferrous phase; If the sum of the mass contents of Fe and S in the main control elements of the particle accounts for more than 99% of the main control elements, the iron-carbon-sulfur-silicon main control phase is an iron sulfide phase; If the sum of the mass contents of Fe, Si and O in the main controlling elements of the particles is greater than 99%, the iron-carbon-sulfur-silicon main controlling phase is FeSiO phase.

6. The method for phase classification of coal combustion fly ash according to claim 3, characterized in that: The step S32, determining the silicon, calcium, and aluminum main phases contained in the particles other than the iron, carbon, sulfur, and silicon main phases, includes: S321, determining whether the sum of the contents of Si, Ca, Al, and O elements contained in the particles other than the iron-carbon-sulfur-silicon main phase is greater than 90%; S322: If yes, then calculate the element content ratio of the element based on the content of Si, Ca and Al in the particles other than the iron, carbon, sulfur and silicon main phases based on a normalization method; the element content ratio is the ratio of the mass content of Si, Ca or Al in the particles to the total mass content of Si, Ca and Al; S323, determining the silicon-calcium-aluminum main controlling phase according to the mass content of the Si, Ca and Al elements and the proportion of the element contents.

7. The method for phase classification of coal combustion fly ash according to claim 6, characterized in that: The calculation method of the element content ratio is: ； Wherein, i represents any one of Si, Ca, and Al; A represents the element content ratio of the element; and W is the mass content of the element in the particles obtained by scanning electron microscope energy spectrum analysis.

8. The method for phase classification of coal combustion fly ash according to claim 6, characterized in that: The calcium-silicon-aluminum main phase includes a Ca-Al-Si transition phase, a Ca-Si wollastonite phase, an aluminum oxide corundum phase, an aluminum silicate phase, a Ca-aluminum silicate phase, a quartz phase and a calcium oxide phase; The step S323, determining the silicon-calcium-aluminum main phase according to the content of the Si, Ca and Al elements and the proportion of the element contents, includes: If W in the particles Si 、W Ca and W Al are between 20% and 50%, and A Si 、A Ca and A Al If both are 0.25, the main silicon-calcium-aluminum phase is a Ca-Al-Si transition phase; If the particles contain A Ca >0.25, and (A Ca +A Si )>0.75, the main silicon-calcium-aluminum phase is Ca-Si wollastonite phase; If W in the particles Al >45%, and A Al >0.75, the main phase of the silicon calcium aluminum is the aluminum oxide corundum phase; If W in the particles Al Between 30% and 40%, and 0.15<A Al <0.50, A Ca <0.05; then the main silicon calcium aluminum phase is aluminosilicate phase; If 0.05≤A Ca <0.25,0.30≤A Si <0.80,0.15≤A Al <0.60, the main silicon-calcium-aluminum phase is a Ca-aluminum silicate phase: If W in the particles Si ≥43%, and meet W Si >60% or A Si ≥0.85, the main phase of the silicon calcium aluminum is the quartz phase: If the particles (W Ca +W O )>80%,(W Al +W Si )<10%,A Ca >0.75, the main phase of the silicon-calcium-aluminum is the calcium oxide phase; Among them, W Si 、W Ca 、W Al and W O Respectively represent the mass contents of Si, Ca, Al and O in the particles obtained by scanning electron microscope energy spectrum analysis; A Si 、A Ca and A Al Respectively represent the proportion of the element content corresponding to Si, Ca and Al elements.

9. The method for phase classification of coal combustion fly ash according to claim 3, characterized in that: The target element sub-phases include high As phase, low As phase, high Ge phase, low Ge phase, high Sb phase and low Sb phase; The method for determining the subclass difference of the target element includes: If 0%<W As ≤3%, then the target element sub-phase is a low As phase; If W in the particles As >3%, the target element sub-phase is a high As phase; If 0%<W Ge ≤1%, then the target element sub-phase is low Ge phase; If W in the particles Ge >1%, the target element sub-phase is a high Ge phase; If 0%<W Sb ≤1%, then the target element sub-phase is a low Sb phase; If W in the particles Sb >1%, the target element sub-phase is a high Sb phase.

10. The method for phase classification of coal combustion fly ash according to claim 1, characterized in that: The step S3, after performing phase classification on the multiple particles contained in the coal combustion fly ash sample according to the contents of the main control element and the target element and determining the phase category to which each particle belongs, further includes: S4, entering the mass content and energy spectrum of the main control element and the target element corresponding to each phase category determined into a mineral analysis system to form an identification database; S5, setting identification parameters in the mineral analysis system so that particles show distinguishable brightness differences in the image; wherein the identification parameters include at least one of magnification, image brightness, and image contrast; S6, using the identification database and the identification parameters, automatically identifying particles in the target sample to be analyzed by the mineral analysis system to obtain identification results of each phase category; S7, if there are unidentified particles in the automatic identification, and the proportion of the unidentified particles exceeds a preset proportion threshold, performing mass content analysis of the main control element and the target element on the unidentified particles to determine whether they can be classified into the existing phase category; S8, if it can be classified into the existing phase category, updating the mass content and energy spectrum of the main control element and the target element corresponding to the phase category in the identification database; S9. If the particle cannot be classified into the existing phase category, a new phase category is determined based on the mass content of the main control element and the target element of the unidentified particle, and the content and energy spectrum of the main control element and the target element of the new phase category are entered into the identification database.

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