A method for determining the occurrence state of lithium ions in coal

Abstract

The present invention provides a method for determining the occurrence state of lithium ions in coal, which belongs to the field of exploration and development of key metals in coal measures. The method solves the problem that existing technical means cannot accurately and comprehensively analyze the occurrence state of key metal lithium in coal. The technical solution comprises the following steps: constructing an organic matter structure model and a mineral structure model of a coal sample, respectively calculating the adsorption sites of lithium ions in the coal sample on the organic matter structure model and the adsorption sites on the mineral structure model, establishing a radial distribution function, respectively calculating the interaction forces between the lithium ions and the organic matter structure model and between the lithium ions and the mineral structure model, respectively calculating the diffusion coefficients of the lithium ions in the organic matter structure model and the mineral structure model, and calculating the diffusion activation energies of the lithium ions in the organic matter structure model and the mineral structure model based on the diffusion coefficients, thereby determining the occurrence state of the lithium ions in the coal sample. The present invention is applicable to exploration of key metals in coal measures.

Description

Technical Field

[0001] The present invention provides a method for determining the occurrence state of lithium ions in coal, and belongs to the technical field of exploration and development of key coal-based metals. Background Art

[0002] Coal is a special sedimentary organic rock. Under the specific geological conditions of its formation, it can be enriched with a variety of metal elements, and then form large or super-large metal deposits in the coal system. The lithium element in coal mainly exists in two forms: mineral-bound and organic-bound. Trace elements in the mineral-bound state exist in minerals through isomorphism, adsorption or impurity mixing, while trace elements in the organic-bound state can exist in different organic coal rock components through complexes, chelates or adsorption. However, lithium has a low atomic number and is scarce in coal, which makes it difficult to accurately measure many conventional analytical methods such as X-ray fluorescence spectrometers and energy spectrometers. This makes it difficult to accurately determine the occurrence state of lithium in coal. The existing technical means for analyzing the occurrence state of lithium in coal have the following problems:

[0003] 1. In-situ analysis technology is limited by the technical bottleneck of accurately identifying the occurrence form of lithium ions. In addition, due to the limitations of the instrument's own performance, it is still difficult to comprehensively and accurately determine the occurrence state of lithium ions in coal through experimental means.

[0004] 2. Indirect methods such as mathematical statistics, step-by-step chemical extraction, and density classification (float-sink experiments) are difficult to accurately distinguish chemical bonding forms such as ion adsorption, organic complexation, and mineral lattice states. They are not only prone to misjudging the occurrence mechanism, but are also subject to interference from complex components such as pyrite and carbonate in coal.

[0005] 3. Traditional spectral techniques, such as inductively coupled plasma mass spectrometry (ICP-MS), can measure the content of lithium ions but cannot provide micro-area distribution information, making it difficult to clearly define the specific occurrence characteristics of lithium ions in coal organic matter micropores, mineral interfaces, or cracks.

[0006] 4. While in situ microscopy techniques such as time-of-flight secondary ion mass spectrometry (ToF-SIMS) and laser ablation-inductively coupled plasma mass spectrometry (LA-ICP-MS) have been applied in research, they face challenges such as difficulty in quantitative analysis, high detection limits, and complex data interpretation. Elemental interference, insufficient spatial resolution, stringent requirements for sample homogeneity, and a reliance on standard samples for quantification, coupled with their destructive nature, also limit their further application. Summary of the Invention

[0007] In order to solve the technical problem that the occurrence state of key metal lithium in coal is difficult to study and existing technical means cannot accurately and comprehensively analyze the occurrence state of lithium ions, the present invention proposes a method for determining the occurrence state of lithium ions in coal.

[0008] In order to solve the above technical problems, the technical solution adopted by the present invention is: comprising the following steps:

[0009] Step S1, determining the element composition and proportion of each element in the coal sample;

[0010] Step S2: 13 C-NMR analysis calculates the bridge-period ratio based on the type and distribution information of aromatic carbon structures and aliphatic carbon structures in the coal sample; FTIR analysis determines the content of various functional groups in the coal sample; XPS analysis determines the occurrence state of carbon, oxygen, nitrogen, and sulfur in the coal sample and their chemical bond characteristics;

[0011] Step S3, constructing an organic matter structure model of the coal sample based on the parameters obtained in Step S1 and Step S2, and constructing a mineral structure model of the coal sample by querying a mineral crystal structure database;

[0012] Step S4, respectively calculating the optimal adsorption sites of lithium ions in the coal sample on the organic matter structure model and the optimal adsorption sites of lithium ions in the coal sample on the mineral structure model;

[0013] Step S5: establishing a radial distribution function to calculate the interaction force between lithium ions and the organic matter structure model and the interaction force between lithium ions and the mineral structure model;

[0014] Step S6, respectively calculating the diffusion coefficient of lithium ions in the organic structure model and the diffusion coefficient of lithium ions in the mineral structure model, and respectively calculating the diffusion activation energy of lithium ions in the organic structure model and the diffusion activation energy of lithium ions in the mineral structure model based on the corresponding diffusion coefficients;

[0015] Step S7: Determine the occurrence state of lithium ions in the coal sample by combining the results of step S4, step S5 and step S6.

[0016] Furthermore, the calculation formula of the bridge-period ratio in step S2 is:

[0017] ;

[0018] Where, X BP is the bridge perimeter ratio of the organic matter structure in the coal sample, is the molar content of protonated aromatic carbon in the total carbon of the coal sample, is the molar content of phenolic carbon and phenol ether carbon in the total carbon of the coal sample, is the molar content of alkyl aromatic carbon in the total carbon of the coal sample, It is the molar content of aromatic bridgehead carbon in the total carbon of the coal sample.

[0019] Furthermore, the method for calculating the optimal adsorption site of lithium ions in the coal sample on the organic matter structure model in step S4 includes the following steps:

[0020] Step S411: Use DMol in Materials Studio software 3 The module uses quantum mechanics methods to obtain the adsorption energy between lithium ions and each functional group in the organic structure model;

[0021] Step S412: comparing the adsorption energies between lithium ions and various functional groups to determine the functional group sites where lithium ions are adsorbed;

[0022] The method for calculating the optimal adsorption site of lithium ions in the coal sample on the mineral structure model in step S4 includes the following steps:

[0023] S421. Using the quantum mechanics method, the CASTEP module in Materials Studio software was used to obtain the adsorption energies between lithium ions and the top, bridge, and acupoints on the mineral structure model.

[0024] Step S422: Compare the adsorption energies between lithium ions and the top sites, bridge sites, and hole sites, respectively, to determine the sites where lithium ions are adsorbed on the mineral structure model.

[0025] Furthermore, the radial distribution function in step 5 is:

[0026] ;

[0027] In the formula, ρ represents the particle number density, r represents the distance between a particle and other particles around it, and n represents the number of coordinated particles existing within a certain range with a particle as the center.

[0028] Furthermore, the calculation formula of the diffusion coefficient in step S6 is:

[0029] ;

[0030] ;

[0031] Where MSD is the root mean square displacement, D is the diffusion coefficient of lithium ions in the coal sample, N is the total number of lithium ions in the coal sample, r i (t) represents the distance between the i-th lithium ion and its central atom at time t, r i (0) represents the distance between the i-th lithium ion and its central atom at the initial moment.

[0032] Furthermore, the calculation formula of the diffusion activation energy in step S6 is:

[0033] ;

[0034] Where D0 is the pre-exponential factor, unit is m 2 / s;

[0035] E D is the diffusion activation energy, unit is kJ / mol;

[0036] R is the ideal gas constant, which is 8.314 J / (mol·K);

[0037] T is the diffusion temperature.

[0038] The beneficial effects of the present invention compared to the prior art are:

[0039] 1. The present invention uses molecular simulation to analyze and determine the occurrence state of lithium ions in coal samples, achieving atomic-level resolution and accurately locating the optimal adsorption sites of lithium ions on the organic matter structure of coal samples and the optimal adsorption sites on the surface of mineral structures. The method has low sample requirements and can deeply reveal the interaction between lithium ions and organic matter structures and mineral structures through simulation calculations, providing key theoretical support for the study of lithium ion resources in coal.

[0040] 2. The present invention digitally quantifies the occurrence state of lithium ions in coal samples by analyzing the adsorption sites of lithium ions on the organic structure of coal samples and the adsorption sites on the mineral structure surface, analyzing the interaction forces between lithium ions and the organic structure model and the interaction forces between lithium ions and the mineral structure model, analyzing the diffusion coefficient of lithium ions in the organic structure model and the diffusion coefficient of lithium ions in the mineral structure model, and analyzing the diffusion activation energy of lithium ions in the organic structure model and the diffusion activation energy of lithium ions in the mineral structure model. This makes the judgment more intuitive and overcomes the problem of inaccurate and incomplete judgment results due to technical limitations compared to the method of judging the occurrence state of lithium ions in coal samples through indirect experimental verification.

[0041] 3. The present invention analyzes and determines the occurrence state of lithium ions in coal samples by molecular simulation method, which can eliminate the influence of heterogeneous substances on the determination of the occurrence state of lithium ions in coal samples, and further improve the accuracy of the determination. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The present invention will be further described below with reference to the accompanying drawings:

[0043] Figure 1 It is a workflow diagram of the present invention;

[0044] Figure 2 Schematic diagram of the distribution of adsorption sites of lithium ions on different functional groups in Jungar No. 6 coal according to the present invention;

[0045] Figure 3Schematic diagram of the adsorption configuration of lithium ions at different sites on the mineral (001) surface of the present invention;

[0046] Figure 4 Schematic diagram of the adsorption configuration of lithium ions at different sites on the (00-1) surface of the mineral according to the present invention;

[0047] Figure 5 Schematic diagram of the distribution characteristics of lithium ion adsorption sites in the mineral structure of the present invention Figure 1 ;

[0048] Figure 6 Schematic diagram of the distribution characteristics of lithium ion adsorption sites in the mineral structure of the present invention Figure 2 ;

[0049] Figure 7 This is a radial distribution function curve diagram between lithium ions and organic matter structure models and mineral structure models at 20°C;

[0050] Figure 8 The radial distribution function curve between lithium ions and organic matter structure model and mineral structure model at 180°C;

[0051] Figure 9 The radial distribution function curve between lithium ions and organic matter structure model and mineral structure model at 300℃;

[0052] Figure 10 Schematic diagram of the change curve of the diffusion coefficient of lithium ions in coal samples with temperature according to the present invention;

[0053] Figure 11 is a graph showing the change of the van der Waals force between lithium ions and silicon atoms with temperature during the adsorption process of lithium ions in the present invention;

[0054] Figure 12 This is a curve diagram showing the change of electrostatic force between lithium ions and silicon atoms with temperature during the lithium ion adsorption process of the present invention. DETAILED DESCRIPTION

[0055] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate relative positions or positional relationships, which are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second" and the like are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, features defined as "first", "second" and the like may explicitly or implicitly include one or more of the features. In the description of the present invention, unless otherwise specified, "multiple" means two or more.

[0056] In the description of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0057] like Figures 1 to 12 As shown, the present invention provides a method for determining the occurrence state of lithium ions in coal, comprising the following steps:

[0058] Step S1: Determine the elemental composition and the proportion of each element in the coal sample.

[0059] Step S2: 13 C-NMR analysis is used to calculate the bridge-period ratio based on the type and distribution information of aromatic carbon structures and aliphatic carbon structures in the coal sample. The calculation formula for the bridge-period ratio is:

[0060] ;

[0061] Where, X BP is the bridge perimeter ratio of the organic matter structure in the coal sample, is the molar content of protonated aromatic carbon in the total carbon of the coal sample, is the molar content of phenolic carbon and phenol ether carbon in the total carbon of the coal sample, is the molar content of alkyl aromatic carbon in the total carbon of the coal sample, is the molar content of aromatic bridgehead carbon in the total carbon of the coal sample;

[0062] Through FTIR analysis, the content of aliphatic functional groups such as hydroxyl, carboxyl, carbonyl, aromatic hydrocarbon functional groups such as benzene ring, and heterocyclic functional groups such as pyrrole and pyridine in coal samples is determined;

[0063] XPS analysis is used to determine the occurrence states and chemical bond characteristics of carbon, oxygen, nitrogen and sulfur in coal samples.

[0064] Step S3: construct an organic matter structure model of the coal sample based on the parameters obtained in steps S1 and S2, and construct a mineral structure model (kaolinite structure model) of the coal sample by querying relevant parameters of the mineral structure model in the American mineral crystal structure database.

[0065] Step S4, respectively calculating the optimal adsorption sites of lithium ions in the coal sample on the organic matter structure model and the optimal adsorption sites of lithium ions in the coal sample on the mineral structure model. The coal sample in this embodiment is Jungar No. 6 coal;

[0066] The method for calculating the optimal adsorption site of lithium ions in coal samples on the organic matter structure model includes the following steps:

[0067] Step S411: Use DMol in Materials Studio software 3 The module uses quantum mechanics to obtain the adsorption energy between lithium ions and each functional group in the organic matter structure model. The adsorption sites of lithium ions on each functional group in Jungar No. 6 coal are as follows: Figure 2 As shown, Figure 2 A represents the adsorption site of lithium ions on the carboxyl group. Figure 2 B represents the adsorption site of lithium ions on the hydroxyl group. Figure 2 C represents the adsorption site of lithium ions on the carbonyl group. Figure 2 D represents the adsorption site of lithium ions on pyridine. Figure 2 E represents the adsorption site of lithium ions on pyrrole. Figure 2 F represents the adsorption site of lithium ions on the benzene ring;

[0068] Step S412: Compare the adsorption energies between the lithium ion and each functional group to determine the functional group site where the lithium ion is adsorbed. This means that the functional group where the lithium ion is adsorbed is determined based on the adsorption energies between the lithium ion and each functional group, thereby determining the optimal adsorption site for the lithium ion on the organic structure model. The adsorption energies of lithium ions on different functional groups on the organic structure model are shown in Table 1 below:

[0069] Table 1 Adsorption energy of lithium ions on different functional groups of organic matter

[0070] ;

[0071] It can be seen from Table 1 that in the organic matter structure, the adsorption energy of different functional groups for lithium ions is, from large to small, carboxyl, hydroxyl, pyrrole, carbonyl, pyridine, and benzene ring. It can be seen that the optimal adsorption site of lithium ions in the organic matter structure of coal samples is near the carboxyl group.

[0072] The method for calculating the optimal adsorption sites of lithium ions in coal samples on a mineral structure model includes the following steps:

[0073] Step S421, using the CASTEP module in Materials Studio software and the quantum mechanics method to calculate the adsorption energies between lithium ions and the top sites, bridge sites, and acupoints on the mineral structure model;

[0074] The adsorption configurations of lithium ions at different sites on the mineral (001) surface are as follows: Figure 3 and Figure 5 As shown, the adsorption configurations of lithium ions at different sites on the mineral (00-1) surface are as follows Figure 4 and Figure 6 As shown, Figure 5 T1, T2, B1, B2, H1, H2 and H3 represent different adsorption sites of lithium ions on the (001) surface of the mineral structure model. Figure 6 T11, B11, B12, H11, H12 and H13 represent different adsorption sites of lithium ions on the (00-1) surface of the mineral structure model. Figure 5 The first column shows the front view of the distribution of different adsorption sites of lithium ions on the (001) surface of the mineral structure model. Figure 5 The second column shows the side view of the distribution of different adsorption sites of lithium ions on the (001) surface of the mineral structure model; Figure 6 The first column shows the front view of the distribution of different adsorption sites of lithium ions on the (00-1) surface of the mineral structure model. Figure 6 The second column shows the side view of the distribution of different adsorption sites of lithium ions on the (00-1) surface of the mineral structure model. The adsorption energy of lithium ions at different adsorption sites on the (001) surface of the mineral structure model is shown in Table 2 below:

[0075] Table 2 Adsorption energy of different adsorption sites on the (001) surface of the mineral structure model

[0076] ;

[0077] The adsorption energy of lithium ions at different adsorption sites on the mineral structure model (00-1) surface is shown in Table 3 below:

[0078] Table 3 Adsorption energy of different adsorption sites on the (00-1) surface of the mineral structure model

[0079] ;

[0080] Step S422: Compare the adsorption energies between lithium ions and the top, bridge, and hole sites to determine the specific site on the mineral structure model where the lithium ions are adsorbed, i.e., determine the optimal adsorption site for lithium ions on the mineral structure model. As shown in Tables 2 and 3 above, the adsorption energy for lithium ions on the (00-1) surface of the mineral structure model is greater than the adsorption energy for lithium ions on the (001) surface of the mineral structure model. This means that the adsorption capacity of the silicon-oxygen tetrahedron layer for lithium ions is greater than that of the aluminum-oxygen octahedron layer in the mineral structure model. The optimal adsorption site for lithium ions on the mineral structure model is hole site H1 on the (00-1) surface of the mineral, located in the center of the oxygen six-membered ring of the silicon-oxygen tetrahedron layer in the mineral structure.

[0081] Step S5: Establish a radial distribution function, calculate the interaction force between lithium ions and the organic structure model and the interaction force between lithium ions and the mineral structure model respectively, and determine the location of lithium ions in the organic structure model and / or the mineral structure model by comparing the interaction force between lithium ions and the organic structure model and the interaction force between lithium ions and the mineral structure model. The radial distribution function is:

[0082] ;

[0083] In the formula, ρ represents the particle number density, r represents the distance between a particle and other particles around it, and n represents the number of coordinated particles existing within a certain range with a particle as the center.

[0084] The radial distribution function curves between lithium ions and organic matter structure models and mineral structure models at different temperatures are as follows: Figures 7 to 9 As shown, the radial distribution function curves for lithium ions and carbon atoms, as well as those for lithium ions and hydrogen atoms, show no distinct peaks. Both the radial distribution function curves for lithium ions and carbon atoms and the radial distribution function curves for hydrogen atoms have g(r)≈1, indicating that the benzene ring and hydrogen atoms have a weak attraction to lithium ions and essentially no interaction. The distance between the lithium ion and nitrogen atom, corresponding to the first peak in the radial distribution function for lithium ions and nitrogen atoms, and the distance between the oxygen atom and lithium ion, corresponding to the first peak in the radial distribution function for lithium ions and oxygen atoms in organic matter, are both 0.185 nm, indicating that hydrogen bonds exist between lithium ions and nitrogen atoms and oxygen atoms in organic matter during adsorption. The r value corresponding to the first peak in the radial distribution function for lithium ions and silicon atoms is 0.405 nm, indicating that van der Waals and electrostatic forces exist between lithium ions and silicon atoms during adsorption.

[0085] like Figures 11 to 12As shown in the figure, when the temperature ranges from 20℃ to 300℃, the electrostatic force varies from -1704.51 to -1729.20 kJ / mol, and the van der Waals force varies from 122.07 to 148.02 kJ / mol. This shows that the van der Waals energy between lithium ions and silicon atoms is relatively weak during the adsorption process, and the electrostatic energy is dominant. The interaction forces between lithium ions and different atoms are shown in Table 4:

[0086] Table 4 Parameters of the radial distribution function curve of lithium ions and different atoms (180℃)

[0087] .

[0088] Step S6: Calculate the diffusion coefficient of lithium ions in the organic structure model and the diffusion coefficient of lithium ions in the mineral structure model respectively to analyze the diffusion and migration mechanism of lithium ions in the organic structure model and the mineral structure model; calculate the diffusion activation energy of lithium ions in the organic structure model and the diffusion activation energy of lithium ions in the mineral structure model at different temperatures according to the corresponding diffusion coefficients to analyze the ease of diffusion of lithium ions in the organic structure model and the mineral structure model. The calculation formula of the diffusion coefficient of lithium ions in the coal sample is:

[0089] ;

[0090] ;

[0091] Where MSD is the root mean square displacement, D is the diffusion coefficient of lithium ions in the coal sample, N is the total number of lithium ions in the coal sample, r i (t) represents the distance between the i-th lithium ion and its central atom at time t, r i (0) represents the distance between the i-th lithium ion and its central atom at the initial moment;

[0092] The calculation formula for diffusion activation energy is:

[0093] ;

[0094] Where D0 is the pre-exponential factor, unit is m 2 / s;

[0095] E D is the diffusion activation energy, unit is kJ / mol;

[0096] R is the ideal gas constant, which is 8.314 J / (mol·K);

[0097] T is the diffusion temperature.

[0098] The curve of the diffusion coefficient of lithium ions in coal samples changing with temperature is as follows: Figure 10 As shown by Figure 10 It can be seen that at 20°C, the diffusion coefficient of lithium ions is 6.6×10-14m2 / s. When the temperature rises to 60°C, the diffusion coefficient of lithium ions increases to 15×10-14m2 / s. After that, the diffusion coefficient of lithium ions continues to decrease with increasing temperature. When the temperature is in the range of 20-60°C, temperature plays a dominant role in the diffusion of lithium ions, and the diffusion coefficient of lithium ions in coal samples increases with increasing temperature. When the temperature is in the range of 60-300°C, the ordering of the coal sample structure causes the diffusion coefficient of lithium ions in the coal sample to decrease. At this time, the effect of temperature change on the diffusion coefficient of lithium ions in the coal sample is smaller than the effect of coal sample structure change on the diffusion coefficient of lithium ions in the coal sample, thereby weakening the diffusion coefficient of lithium ions in the coal sample.

[0099] Step S7: Determine the occurrence state of lithium ions in the coal sample by combining the results of step S4, step S5, and step S6, that is, determine whether the lithium ions in the coal sample are in a mineral-bound state or an organic-bound state.

[0100] In this embodiment, according to the optimal adsorption sites of lithium ions in the organic matter structure of the coal sample and on the mineral structure model, the peak distribution of the radial distribution function between lithium ions and each particle, and the change in the diffusion coefficient of lithium ions in the coal sample with temperature obtained in steps S4, S5 and S6, it can be known that the occurrence state of lithium ions in the coal sample is mainly mineral-bound.

[0101] The working principle of the present invention is:

[0102] Through molecular simulation methods, the organic matter structure model and mineral structure model of the coal sample were established respectively, and the optimal adsorption sites of lithium ions on the organic matter structure model and the mineral structure model were analyzed respectively. The molecular dynamics method was used to analyze the interaction relationship between lithium ions and the organic matter structure model and the mineral structure model in the coal sample respectively. The diffusion activation energy of lithium ions in the organic matter structure model and the diffusion activation energy of lithium ions in the mineral structure model were calculated at different temperatures respectively. According to the optimal adsorption sites of lithium ions and the interaction relationship between lithium ions and the organic matter structure model and the mineral structure model, as well as the diffusion characteristics of lithium ions during the heating process, the enrichment and distribution mechanism of lithium ions in the coal sample was determined, providing a basis for analyzing the occurrence state of lithium ions in the coal sample.

[0103] Regarding the specific structure of the present invention, it should be noted that the connection relationship between the various component modules adopted in the present invention is definite and feasible. Except for those specifically described in the embodiments, the specific connection relationship can bring about corresponding technical effects and solve the technical problems raised by the present invention without relying on the execution of corresponding software programs. The components, modules, models of specific components appearing in the present invention, the connection methods between each other, and the conventional usage methods and expected technical effects brought about by the above-mentioned technical features, except for those specifically described, all belong to the disclosed contents in patents, journal articles, technical manuals, technical dictionaries, and textbooks that can be obtained by technical personnel in this field before the application date, or belong to the existing technologies such as conventional technology and common knowledge in this field. There is no need to elaborate, so that the technical solution provided in this case is clear, complete, and feasible, and the corresponding physical products can be reproduced or obtained based on this technical means.

[0104] 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 determining the occurrence state of lithium ions in coal, characterized in that: The following steps are involved: Step S1, determining the element composition and proportion of each element in the coal sample; Step S2: 13 C-NMR analysis calculates the bridge-period ratio based on the type and distribution information of aromatic carbon structures and aliphatic carbon structures in the coal sample; FTIR analysis determines the content of various functional groups in the coal sample; XPS analysis determines the occurrence state of carbon, oxygen, nitrogen, and sulfur in the coal sample and their chemical bond characteristics; Step S3, constructing an organic matter structure model of the coal sample based on the parameters obtained in Step S1 and Step S2, and constructing a mineral structure model of the coal sample by querying a mineral crystal structure database; Step S4, respectively calculating the optimal adsorption sites of lithium ions in the coal sample on the organic matter structure model and the optimal adsorption sites of lithium ions in the coal sample on the mineral structure model; Step S5: establishing a radial distribution function to calculate the interaction force between lithium ions and the organic matter structure model and the interaction force between lithium ions and the mineral structure model; Step S6, respectively calculating the diffusion coefficient of lithium ions in the organic structure model and the diffusion coefficient of lithium ions in the mineral structure model, and respectively calculating the diffusion activation energy of lithium ions in the organic structure model and the diffusion activation energy of lithium ions in the mineral structure model based on the corresponding diffusion coefficients; Step S7: Determine the occurrence state of lithium ions in the coal sample by combining the results of step S4, step S5 and step S6.

2. The method for determining the occurrence state of lithium ions in coal according to claim 1, characterized in that: The calculation formula of the bridge circumference ratio in step S2 is: ； Where, X BP is the bridge perimeter ratio of the organic matter structure in the coal sample, is the molar content of protonated aromatic carbon in the total carbon of the coal sample, is the molar content of phenolic carbon and phenol ether carbon in the total carbon of the coal sample, is the molar content of alkyl aromatic carbon in the total carbon of the coal sample, It is the molar content of aromatic bridgehead carbon in the total carbon of the coal sample.

3. The method for determining the occurrence state of lithium ions in coal according to claim 1, wherein: The method for calculating the optimal adsorption site of lithium ions in the coal sample on the organic matter structure model in step S4 includes the following steps: Step S411: Use DMol in Materials Studio software 3 The module uses quantum mechanics methods to obtain the adsorption energy between lithium ions and each functional group in the organic structure model; Step S412: comparing the adsorption energies between lithium ions and various functional groups to determine the functional group sites where lithium ions are adsorbed; The method for calculating the optimal adsorption site of lithium ions in the coal sample on the mineral structure model in step S4 includes the following steps: S421. Using the quantum mechanics method, the CASTEP module in Materials Studio software was used to obtain the adsorption energies between lithium ions and the top, bridge, and acupoints on the mineral structure model. Step S422: Compare the adsorption energies between lithium ions and the top sites, bridge sites, and hole sites, respectively, to determine the sites where lithium ions are adsorbed on the mineral structure model.

4. The method for determining the occurrence state of lithium ions in coal according to claim 1, wherein: The radial distribution function in step 5 is: ； In the formula, ρ represents the particle number density, r represents the distance between a particle and other particles around it, and n represents the number of coordinated particles existing within a certain range with a particle as the center.

5. The method for determining the occurrence state of lithium ions in coal according to claim 1, wherein: The calculation formula of the diffusion coefficient in step S6 is: ； ； Where MSD is the root mean square displacement, D is the diffusion coefficient of lithium ions in the coal sample, N is the total number of lithium ions in the coal sample, r i (t) represents the distance between the i-th lithium ion and its central atom at time t, r i (0) represents the distance between the i-th lithium ion and its central atom at the initial moment.

6. The method for determining the occurrence state of lithium ions in coal according to claim 5, characterized in that: The calculation formula of the diffusion activation energy in step S6 is: ； Where D0 is the pre-exponential factor, unit is m 2 / s; E D is the diffusion activation energy, unit is kJ / mol; R is the ideal gas constant, which is 8.314 J / (mol·K); T is the diffusion temperature.

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