A method, system, device and medium for determining the content of ion-adsorbed rare earths

Abstract

The present application relates to rare earth resources exploration technical field, specifically to a kind of ion adsorption type rare earth content determination method, system, equipment and medium, the method by constructing the quantitative relationship prediction model between the normalized charge rate and total rare earth oxide mass fraction, impedance measurement system is arranged in study area, impedance amplitude and phase are collected, normalized charge rate is obtained based on impedance amplitude and phase, the quantitative relationship prediction model between the normalized charge rate and total rare earth oxide mass fraction is constructed, and total rare earth oxide mass fraction is calculated based on quantitative relationship prediction model.The present application method considers the surface electrical property influence of ion adsorption type rare earth ore sample, establishes the correlation between frequency spectrum induced polarization response and chemical parameter, and estimates the rare earth oxide content in ion adsorption type rare earth sample using it.

Description

Technical Field

[0001] This invention relates to the field of rare earth resource exploration technology, and in particular to an ion adsorption method, system, equipment and medium for determining rare earth content. Background Technology

[0002] Rare earth elements are key components of many advanced technologies in defense, aerospace, and new energy fields. Ion adsorption rare earth resource exploration heavily relies on shallow wells, shallow drilling, and chemical analysis techniques. Traditional drilling methods suffer from limited depth, high cost, and low borehole coverage, while chemical analysis methods are costly, time-consuming, and destructive, making rapid surveys and real-time monitoring difficult.

[0003] Spectral induced polarization (SIP) method measures the complex resistivity spectrum of rocks and soils over a wide frequency band (typically mHz to kHz) to obtain electrical parameters related to the medium's pore structure, mineral composition, and ion concentration. According to the mineralization mechanism of ion-adsorption rare earth deposits, rare earth ions migrate and transport with acidic fluids, are adsorbed onto clay minerals, and enriched in the weathering layer, with light and heavy rare earth enrichment exhibiting stratification. The formation of a stable electrical bilayer at the clay-water interface helps to establish the relationship between surface adsorption and physical properties, while the ion concentration in the solution affects the conductivity of the underground medium. Based on the main electrical parameters—resistivity (conductivity), polarizability, and other physical properties—of samples at different depths in the weathering profile of ion-adsorption rare earth deposits, this study investigates the response relationship between rare earth oxide content and electrical parameters in weathering profile soil samples. This can provide a theoretical basis and technical support for the development and implementation of a comprehensive physical and chemical exploration technology system for ion-adsorption rare earth deposits.

[0004] While methods such as resistivity tomography and seismic refraction are helpful in guiding the location distribution of rare earth ore boreholes and characterizing weathered layers, current techniques often overlook the contribution of surface electrical properties to overall conductivity. Secondly, the complex conductivity of a sample reflects the superposition of polarization responses at different scales, such as low-frequency film polarization, mid-frequency Stern layer polarization and diffusion layer polarization, and high-frequency Maxwell-Wagner polarization. Ion-adsorbed rare earth ore exhibits a "lighter at the top, heavier at the bottom" stratified enrichment characteristic in weathered layers, and the two column packing methods for soil samples lead to different ionic states in the samples. Specifically, introducing water into a dry sample causes ions to concentrate in the electric bilayer at the clay-water interface, while pre-mixing the solution with the sample causes some ions to diffuse. Therefore, the polarization length distribution in water-bearing soil samples is complex and it is difficult to distinguish between different polarization mechanisms. Although the Cole-Cole model is widely used to explain the spectral induced electrical response of rocks and minerals, a single model cannot accurately describe the polarization caused by the electric double layer in ion-adsorbed rare earth mineral samples at different depths. Therefore, it is necessary to select an appropriate model for fitting based on the sample state and spectral characteristics, and then establish the response relationship between rare earth content and physical property parameters in ion-adsorbed rare earth minerals.

[0005] Therefore, it is necessary to provide an ion adsorption-based rare earth content determination method, system, equipment, and medium that can effectively fit the signal, accurately extract the electrical parameters related to rare earth content, and establish a reliable quantitative relationship to solve the above-mentioned technical problems. Summary of the Invention

[0006] The purpose of this invention is to provide an ion adsorption method, system, equipment, and medium for determining rare earth content. The specific technical solution is as follows:

[0007] An ion adsorption-type rare earth content determination method involves setting up an impedance measurement system in the study area to collect impedance amplitude and phase, obtaining the normalized charge rate based on the impedance amplitude and phase, constructing a quantitative relationship prediction model between the normalized charge rate and the total rare earth oxide mass fraction, and calculating the total rare earth oxide mass fraction based on the quantitative relationship prediction model.

[0008] The process of constructing a quantitative relationship prediction model includes:

[0009] S1: Select the study area and collect weathering profile samples of ion adsorption type rare earth minerals according to the underground depth;

[0010] S2: Pre-treatment of the collected samples by air drying, crushing and grinding;

[0011] S3: Prepare the sample to be tested and perform spectral induced polarization measurements, as follows:

[0012] S3.1 Prepare a soil column device with a bottom inlet and a top outlet, and install power supply electrodes at the bottom and top of the soil column device, and install measuring electrodes at symmetrical positions on the upper and lower sides of the side wall of the soil column device.

[0013] S3.2. The sample after step S2 is filled into the sample cavity of the soil column device using both dry and wet methods, and an electrolyte solution is introduced through the bottom water inlet to form a soil column containing the sample that can be measured.

[0014] S3.3 Connect the power supply electrode and the measuring electrode to the impedance analyzer, and use the four-electrode method to measure the complex resistivity spectrum of the soil column containing the sample within a preset frequency range to obtain the impedance amplitude and phase at multiple frequencies.

[0015] S4: Based on the complex resistivity spectrum obtained in step S3, and combined with the measurement conditions of dry and wet methods, a preset Cole-Cole model is selected to fit the spectral data, and model parameters including at least charge rate and zero-frequency resistivity are obtained through inversion calculation.

[0016] S5: Based on the model parameters obtained from step S4, calculate the normalized charge rate that characterizes the electrochemical polarization intensity of the sample.

[0017] S6: Using calibrated samples with known rare earth oxide content, establish a quantitative relationship prediction model between the normalized charge rate and the total rare earth oxide mass fraction.

[0018] Specifically, in S1, select 3-5 typical ion-adsorption type rare earth mineral weathering profiles. When sampling, take several blocky humus layer, soil layer, fully weathered layer and semi-weathered layer samples from top to bottom of the weathering profile at the same interval.

[0019] Specifically, in S4, the process of fitting the spectral data is as follows:

[0020] First, we compared and analyzed the measurement data of dry column packing and wet column packing, and then performed fitting in the following three cases;

[0021] The first scenario involves the absolute phase values ​​measured by both dry and wet column packing methods. If the absolute phase value changes with increasing frequency at frequencies greater than 100 Hz, it indicates the presence of wideband Maxwell-Wagner polarization interference in the sample. A dual Cole-Cole model is then used to fit the data. The expression for the dual Cole-Cole model is as follows:

[0022] ;

[0023] in, For complex resistivity, The imaginary unit, This is the impedance amplitude. For phase, Angular frequency, To measure frequency, Resistivity at zero frequency , Indicates charge rate, , Represents the Cole-Cole exponent. , The subscripts 1 and 2 indicate the Cole-Cole relaxation time, and are used to distinguish the different polarization mechanisms in the double Cole-Cole model.

[0024] The second method involves measuring data from samples taken from deeper formations. If the absolute phase value measured using either dry or wet column packing methods reaches its maximum or minimum value within the 100-1000 Hz frequency range, or if the change in absolute phase value decreases with increasing frequency, then the sample is considered to contain characteristic peaks of coupled polarization between the Stern layer and the diffuse layer, appearing within this range. Signals interfered with by high frequencies are discarded, and spectral data close to the characteristic peak frequency is extracted. A single Cole-Cole model is used to fit the data. The expression for the single Cole-Cole model is as follows:

[0025] ;

[0026] in, For charge rate, The Cole-Cole exponent. Cole-Cole relaxation time;

[0027] The third case involves a characteristic peak frequency of less than 100Hz for the absolute value of the phase measured under dry column packing, while a steep rise occurs at high frequencies under wet column packing. The dry column packing data is fitted using a single Cole-Cole model, while the wet column packing data is fitted using a double Cole-Cole model.

[0028] Substitute the spectral data into the model, and solve for each model parameter using the nonlinear least squares inversion fitting method.

[0029] Specifically, in S5, the calculation process for the normalized charge rate includes:

[0030] In the double Cole-Cole model, the normalized charge rate is obtained by dividing the charge rate by the zero-frequency resistivity. , The normalized charge rate in the low-frequency Cole-Cole term with a longer relaxation time is used as a parameter to describe the magnitude of the electric double-layer polarization.

[0031] In the single Cole-Cole model, the normalized charge rate is obtained by dividing the charge rate by the zero-frequency resistivity. ;

[0032] in, Mn The normalized charge rate is represented by the subscripts 1 and 2, which are used to distinguish the different polarization mechanisms in the double Cole-Cole model.

[0033] Specifically, in S6, the process of establishing a quantitative relationship prediction model includes:

[0034] A quantitative relationship prediction model between charge rate and total rare earth oxide mass fraction was established by fitting measurement data obtained under wet and dry column packing methods. The expression is as follows:

[0035] ;

[0036] in, REO This represents the mass fraction of total rare earth oxides. a , b The model parameters were obtained by performing linear regression on a set of calibration samples with known total rare earth oxide mass fractions.

[0037] A quantitative predictive model for the relationship between normalized charge rate and total rare earth oxide mass fraction obtained by fitting measurement data under wet-filled column conditions was established, directly correlating rare earth oxide content and electrical parameters under fully saturated conditions.

[0038] ;

[0039] in, γ , δ The model parameters are obtained by performing linear regression on a set of calibration samples with known total rare earth oxide mass fractions.

[0040] Specifically, after establishing a quantitative relationship prediction model, it also includes:

[0041] S7. Model reliability test: The model reliability test is performed in sequence by testing the model fitting index, cross-validation with leave-one-out method and comparison method. If all the above tests are passed, the model reliability test is passed.

[0042] Model fit index verification: Calculate the relative root mean square error of the model fit. The relative root mean square error of the amplitude is less than 4.5% and the relative root mean square error of the phase is less than 15%. If the above indexes are not met, the model is refitted.

[0043] Comparison method: Sample and use a quantitative relationship prediction model to predict the total rare earth oxide mass fraction. Compare the prediction results with the results of standard chemical analysis methods. If the average relative error is less than 15%, the model is considered to have passed the test; otherwise, the model is refitted.

[0044] In addition, the present invention also provides an ion adsorption type rare earth content determination system, including a soil column device, an electrode group and a full waveform impedance analyzer;

[0045] The soil column device includes a sample chamber, a bottom water inlet, and a top water outlet, with the bottom water inlet and top water outlet respectively located at the top and bottom of the sample chamber.

[0046] The electrode assembly includes a power supply electrode and a measuring electrode. The power supply electrode is disposed at the top and bottom of the sample chamber, and the measuring electrode is disposed on the side wall of the sample chamber.

[0047] The full-waveform impedance analyzer is electrically connected to the electrode group and is used to measure the complex resistivity spectrum of the soil column containing the sample within a preset frequency range using the four-electrode method.

[0048] In addition, the present invention also provides a computer device, including a memory and a processor;

[0049] The memory is used to store computer programs that can run on the processor;

[0050] The processor is used to execute the computer program to implement the steps of the ion adsorption type rare earth content determination method as described above.

[0051] In addition, the present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the ion adsorption type rare earth content determination method described above.

[0052] The application of the technical solution of the present invention has at least the following beneficial effects:

[0053] This invention provides a method for determining the content of rare earth elements through ion adsorption. Considering the influence of the surface electrical properties of ion-adsorbed rare earth mineral samples, it establishes a correlation between the spectral induced polarization response and chemical parameters, and uses this correlation to estimate the content of rare earth oxides in the ion-adsorbed rare earth samples. This method can effectively extract electrical parameters directly related to rare earth content by selecting an appropriate model fitting scheme based on the sample state, depth, and spectral characteristics, and it also distinguishes strata with different physicochemical properties in weathered profiles.

[0054] Compared with traditional chemical methods for content determination, the method of this invention has the advantages of being fast, non-destructive, environmentally friendly, and low-cost. The method of this invention can be used to directly and preliminarily assess the content of rare earth oxides and the spatial distribution of rare earth mineralization in the ground in the field.

[0055] In addition to the objectives, features, and advantages described above, the present invention has other objectives, features, and advantages. The invention will now be described in further detail with reference to the figures. Attached Figure Description

[0056] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0057] Figure 1 This is a flowchart of the steps of the ion adsorption type rare earth content determination method in a preferred embodiment of the present invention;

[0058] Figure 2 This is a schematic diagram of the ion adsorption type rare earth content determination system in a preferred embodiment of the present invention;

[0059] Wherein, 1-first sidewall insertion hole, 2-second sidewall insertion hole, 3-bottom power supply electrode, 4-top power supply electrode, 5-sample chamber, 6-bottom water inlet, 7-top water outlet. Detailed Implementation

[0060] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0061] Example:

[0062] like Figure 1 As shown, this embodiment provides a method for determining rare earth content based on spectral induced polarization:

[0063] An impedance measurement system was deployed in the study area to collect impedance amplitude and phase. Based on the impedance amplitude and phase, the normalized charge rate was obtained. A quantitative relationship prediction model between the normalized charge rate and the total rare earth oxide mass fraction was constructed. The total rare earth oxide mass fraction was calculated based on the quantitative relationship prediction model.

[0064] Furthermore, the process by which the impedance measurement system acquires the impedance amplitude and phase is as follows:

[0065] Electrodes were laid out at equal intervals along the research area and connected to a multi-channel field impedance measurement system via cables. The impedance amplitude and phase of each unit at a preset frequency were collected using a pseudo-Weiner sequence. After removing outliers, the charge rate and normalized charge rate could be obtained by fitting the data.

[0066] The process of constructing a quantitative relationship prediction model includes (S1 to S7):

[0067] S1: Select the study area and collect weathering profile samples of ion adsorption type rare earth minerals according to the underground depth.

[0068] In this embodiment, 3-5 typical ion-adsorption type rare earth mineral weathering profiles are selected. When sampling, several blocky humus layer, soil layer, fully weathered layer and semi-weathered layer samples are taken from top to bottom of the weathering profile at the same interval.

[0069] S2: Pre-treatment of the collected samples by air drying, crushing and grinding.

[0070] S3: Prepare the sample to be tested and perform spectral induced polarization measurements, as follows:

[0071] S3.1 Prepare a soil column device with a bottom inlet and a top outlet, and install power supply electrodes at the bottom and top of the soil column device, and install measuring electrodes at symmetrical positions on the upper and lower sides of the side wall of the soil column device.

[0072] S3.2. The sample after step S2 is filled into the sample cavity of the soil column device using both dry and wet methods, and an electrolyte solution is introduced through the bottom water inlet to form a soil column containing the sample that can be measured.

[0073] S3.3 Connect the power supply electrode and the measuring electrode to the impedance analyzer, and use the four-electrode method to measure the complex resistivity spectrum of the soil column containing the sample within a preset frequency range to obtain the impedance amplitude and phase at multiple frequencies.

[0074] It should be noted that the preferred preset frequency range in this embodiment is 0.001-1000Hz. This range is based on the widest frequency setting range that the impedance analyzer can achieve. Secondly, this is an important frequency band where electrochemical polarization signals appear. Higher frequency signals may mask the low-frequency electrochemical polarization signals of interest, while lower frequency film polarization will also cause signal interference.

[0075] In S3.2, the soil column device is filled with samples using both dry and wet methods. The dry filling method involves first filling the sample cavity with the sample processed in step S2, then introducing an electrolyte solution into the soil column device through the bottom inlet and expelling the air from the soil column device through the top outlet until the liquid level reaches the top of the soil column device, ensuring that the electrolyte solution is in full contact with the electrodes. The wet filling method involves pre-mixing the sample processed in step S2 with the electrolyte solution and removing excess air by vacuuming, then filling the sample cavity with the mixture, and using the electrolyte solution to fill the excess space in the soil column, ensuring that the electrolyte solution is in full contact with the electrodes.

[0076] S4: Based on the complex resistivity spectrum obtained in step S3, and combined with the measurement conditions of dry and wet methods, a preset Cole-Cole model is selected to fit the spectral data, and model parameters including at least charge rate and zero-frequency resistivity are obtained through inversion calculation.

[0077] Specifically, in this embodiment, copper electrode plates are used as power supply electrodes A and B, and non-polarized electrodes are used as measurement electrodes M and N. The copper electrode plates and non-polarized electrodes are connected to a full-waveform impedance analyzer, where AM=NB=5cm and MN=7cm. The complex resistivity spectrum of the sample is measured in the range of 0.001 to 1000Hz using a laboratory SIP measurement system to obtain the impedance amplitude (Ω∙m) at multiple frequencies and the phase (rad) between the injected signal and the measured signal.

[0078] Furthermore, based on the sample's state, depth location, and spectral characteristics, the data were analyzed and a model fitting scheme was selected. First, the measurement data of dry column packing and wet column packing were compared and analyzed, and the fitting was performed in the following three cases.

[0079] The first scenario involves the absolute phase values ​​measured by both dry and wet column packing methods. If the absolute phase value changes with increasing frequency at frequencies greater than 100 Hz, it indicates the presence of wideband Maxwell-Wagner polarization interference in the sample. A dual Cole-Cole model is then used to fit the data. The expression for the dual Cole-Cole model is as follows:

[0080] ;

[0081] in, For complex resistivity, The imaginary unit, This is the impedance amplitude. For phase, Angular frequency, To measure frequency, Resistivity at zero frequency , Indicates charge rate, , Represents the Cole-Cole exponent. , The subscripts 1 and 2 indicate the Cole-Cole relaxation time, and are used to distinguish the different polarization mechanisms in the double Cole-Cole model.

[0082] The second method involves measuring data from samples taken from deeper formations. If the absolute phase value measured using either dry or wet column packing methods reaches its maximum or minimum value within the 100-1000 Hz frequency range, or if the change in absolute phase value decreases with increasing frequency, then the sample is considered to contain characteristic peaks of coupled polarization between the Stern layer and the diffuse layer, appearing within this range. Signals interfered with by high frequencies are discarded, and spectral data close to the characteristic peak frequency is extracted. A single Cole-Cole model is used to fit the data. The expression for the single Cole-Cole model is as follows:

[0083] ;

[0084] in, For charge rate, The Cole-Cole exponent. Cole-Cole relaxation time;

[0085] The third case involves a characteristic peak frequency of less than 100Hz for the absolute value of the phase measured under dry column packing, while a steep rise occurs at high frequencies under wet column packing. The dry column packing data is fitted using a single Cole-Cole model, while the wet column packing data is fitted using a double Cole-Cole model.

[0086] Substitute the spectral data into the model, and solve for each model parameter using the nonlinear least squares inversion fitting method.

[0087] S5: Based on the model parameters obtained from step S4, calculate the normalized charge rate that characterizes the electrochemical polarization intensity of the sample.

[0088] In this embodiment, the calculation process of the normalized charge rate includes:

[0089] In the double Cole-Cole model, the normalized charge rate is obtained by dividing the charge rate by the zero-frequency resistivity. , The normalized charge rate in the low-frequency Cole-Cole term with a longer relaxation time is used as a parameter to describe the magnitude of the electric double-layer polarization.

[0090] In the single Cole-Cole model, the normalized charge rate is obtained by dividing the charge rate by the zero-frequency resistivity. ;

[0091] in, Mn The normalized charge rate is represented by the subscripts 1 and 2, which are used to distinguish the different polarization mechanisms in the double Cole-Cole model.

[0092] S6: Using calibrated samples with known rare earth oxide content, establish a quantitative relationship prediction model between the normalized charge rate and the total rare earth oxide mass fraction.

[0093] In this embodiment, the process of establishing the quantitative relationship prediction model includes:

[0094] A quantitative relationship prediction model between charge rate and total rare earth oxide mass fraction was established by fitting measurement data obtained under wet and dry column packing methods. The expression is as follows:

[0095] ;

[0096] in, REO This represents the mass fraction of total rare earth oxides. a , b The model parameters were obtained by performing linear regression on a set of calibration samples with known total rare earth oxide mass fractions.

[0097] A quantitative predictive model for the relationship between normalized charge rate and total rare earth oxide mass fraction obtained by fitting measurement data under wet-filled column conditions was established, directly correlating rare earth oxide content and electrical parameters under fully saturated conditions.

[0098] ;

[0099] in, γ , δ The model parameters are obtained by performing linear regression on a set of calibration samples with known total rare earth oxide mass fractions.

[0100] S7. Model reliability test: The model reliability test is performed in sequence by testing the model fitting index, cross-validation with leave-one-out method and comparison method. If all the above tests are passed, the model reliability test is passed.

[0101] Model fit index verification: Calculate the relative root mean square error of the model fit. The relative root mean square error of the amplitude is less than 4.5% and the relative root mean square error of the phase is less than 15%. If the above indexes are not met, the model is refitted.

[0102] Comparison method: Sample and use a quantitative relationship prediction model to predict the total rare earth oxide mass fraction. Compare the prediction results with the results of standard chemical analysis methods (such as ICP-MS). If the average relative error is less than 15%, the model is considered to have passed the test; otherwise, the model is refitted.

[0103] Furthermore, in the model fitting index test, the index is considered qualified if the relative root mean square error of the amplitude is less than 4.5% and the relative root mean square error of the phase is less than 15%. In some strict scenarios, the index can also be considered excellent if the relative root mean square error of the amplitude is less than 1.5% and the relative root mean square error of the phase is less than 5%.

[0104] This embodiment provides a method for determining the content of rare earth elements through ion adsorption. By considering the influence of the surface electrical properties of ion-adsorbed rare earth mineral samples, a correlation is established between the spectral induced polarization response and chemical parameters. This correlation is then used to estimate the content of rare earth oxides in ion-adsorbed rare earth samples, enabling rapid measurement of rare earth oxide content. This method can effectively extract electrical parameters directly related to rare earth content by selecting an appropriate model fitting scheme based on sample state, depth, and spectral characteristics, and it also distinguishes strata with different physicochemical properties in weathered profiles.

[0105] In addition, such as Figure 2 As shown, this embodiment also provides an ion adsorption type rare earth content determination system, including a soil column device, an electrode group and a full waveform impedance analyzer;

[0106] The soil column device includes a sample chamber 5, a bottom water inlet 6, and a top water outlet 7, with the bottom water inlet 6 and the top water outlet 7 respectively located at the top and bottom of the sample chamber 5.

[0107] The electrode assembly includes a power supply electrode and a measuring electrode, wherein the power supply electrode is disposed at the top and bottom of the sample chamber (e.g., ...). Figure 2 The bottom power supply electrode 3 and the top power supply electrode 4 shown are used to measure the electrode, which is disposed on the side wall of the sample chamber.

[0108] The full-waveform impedance analyzer is electrically connected to the electrode group and is used to measure the complex resistivity spectrum of the soil column containing the sample within a preset frequency range using the four-electrode method.

[0109] Specifically, the soil column device in this embodiment is made of acrylic material, is 17cm high, has an inner diameter of 4cm for the sample chamber, a threaded cap on the top, and insertion holes on the side walls (e.g., Figure 2 The first sidewall socket 1 and the second sidewall socket 2 shown are used to install measuring electrodes.

[0110] Furthermore, in this embodiment, the power supply electrode is a copper electrode plate, and the measurement electrode is a non-polarized electrode.

[0111] In this embodiment, the full-waveform impedance analyzer obtains the impedance amplitude and the phase (rad) between the injected signal and the measured signal by injecting a sinusoidal current into two power supply electrodes and acquiring the measured potential difference between the two measuring electrodes at multiple frequencies (mHz to kHz). The full-waveform impedance analyzer is also connected to a computer device to transmit the obtained impedance amplitude and phase data to the computer device for analysis and processing.

[0112] In addition, this embodiment also provides a computer device, including a memory and a processor;

[0113] The memory is used to store computer programs that can run on the processor;

[0114] The processor is used to execute the computer program to implement the steps of the ion adsorption type rare earth content determination method as described above.

[0115] It should be noted that computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof. These programming languages ​​include object-oriented programming languages—such as Java, Smalltalk, and C++—as well as conventional procedural programming languages—such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0116] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0117] In addition, this embodiment also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the ion adsorption type rare earth content determination method described above.

[0118] The readable storage medium provided in this application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., a computer program) for executing the above-described ion adsorption type rare earth content determination method. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the ion adsorption type rare earth content determination method provided in the above embodiments, and will not be repeated here.

[0119] The above description is only a preferred embodiment of the present invention and does not limit the scope of the present invention. All equivalent structural transformations made under the inventive concept of the present invention using the contents of the present invention specification and drawings, or direct / indirect applications in other related technical fields, are included within the protection scope of the present invention.

Claims

1. A method for determining rare earth content using ion adsorption, characterized in that, An impedance measurement system was set up in the study area to collect impedance amplitude and phase. Based on the impedance amplitude and phase, the normalized charge rate was obtained. A quantitative relationship prediction model between the normalized charge rate and the total rare earth oxide mass fraction was constructed. The total rare earth oxide mass fraction was calculated based on the quantitative relationship prediction model. The process of constructing a quantitative relationship prediction model includes: S1: Select the study area and collect weathering profile samples of ion adsorption type rare earth minerals according to the underground depth; S2: Pre-treatment of the collected samples by air drying, crushing and grinding; S3: Prepare the sample to be tested and perform spectral induced polarization measurements, as follows: S3.1 Prepare a soil column device with a bottom inlet and a top outlet, and install power supply electrodes at the bottom and top of the soil column device, and install measuring electrodes at symmetrical positions on the upper and lower sides of the side wall of the soil column device. S3.

2. The sample after step S2 is filled into the sample chamber of the soil column device using both dry and wet methods, and an electrolyte solution is introduced through the bottom inlet to form a soil column containing the sample for measurement. The dry method involves first filling the sample chamber with the sample after step S2, then introducing the electrolyte solution into the soil column device through the bottom inlet and expelling the air from the soil column device through the top outlet until the liquid level reaches the top of the soil column device, ensuring that the electrolyte solution is in full contact with the electrodes. The wet method involves pre-mixing the sample after step S2 with the electrolyte solution and removing excess air by vacuuming, then filling the sample chamber with the mixture, and using the electrolyte solution to fill the excess space in the soil column, ensuring that the electrolyte solution is in full contact with the electrodes. S3.3 Connect the power supply electrode and the measuring electrode to the impedance analyzer, and use the four-electrode method to measure the complex resistivity spectrum of the soil column containing the sample within a preset frequency range to obtain the impedance amplitude and phase at multiple frequencies. S4: Based on the complex resistivity spectrum obtained in step S3, and combined with the measurement conditions of dry and wet methods, a preset Cole-Cole model is selected to fit the spectral data, and model parameters including at least charge rate and zero-frequency resistivity are obtained through inversion calculation. S5: Based on the model parameters obtained from step S4, calculate the normalized charge rate that characterizes the electrochemical polarization intensity of the sample. S6: Using calibrated samples with known rare earth oxide content, establish a quantitative relationship prediction model between the normalized charge rate and the total rare earth oxide mass fraction.

2. The method for determining rare earth content by ion adsorption as described in claim 1, characterized in that, In S1, select 3-5 typical ion adsorption type rare earth mineral weathering profiles. When sampling, take several blocky humus layer, soil layer, fully weathered layer and semi-weathered layer samples from top to bottom of the weathering profile at the same interval.

3. The method for determining rare earth content by ion adsorption as described in claim 2, characterized in that, In S4, the process of fitting the spectral data is as follows: First, we compared and analyzed the measurement data of dry column packing and wet column packing, and then performed fitting in the following three cases; The first scenario involves the absolute phase values ​​measured by both dry and wet column packing methods. If the absolute phase value changes with increasing frequency at frequencies greater than 100 Hz, it indicates the presence of wideband Maxwell-Wagner polarization interference in the sample. A dual Cole-Cole model is then used to fit the data. The expression for the dual Cole-Cole model is as follows: ； in, For complex resistivity, The imaginary unit, This is the impedance amplitude. For phase, Angular frequency, To measure frequency, Resistivity at zero frequency , Indicates charge rate, , Represents the Cole-Cole exponent. , The subscripts 1 and 2 indicate the Cole-Cole relaxation time, and are used to distinguish the different polarization mechanisms in the double Cole-Cole model. The second method involves measuring data from samples taken from deeper formations. If the absolute phase value measured using either dry or wet column packing methods reaches its maximum or minimum value within the 100-1000 Hz frequency range, or if the change in absolute phase value decreases with increasing frequency, then the sample is considered to contain characteristic peaks of coupled polarization between the Stern layer and the diffuse layer, appearing within this range. Signals interfered with by high frequencies are discarded, and spectral data close to the characteristic peak frequency is extracted. A single Cole-Cole model is used to fit the data. The expression for the single Cole-Cole model is as follows: ； in, For charge rate, The Cole-Cole exponent. Cole-Cole relaxation time; The third case involves a characteristic peak frequency of less than 100Hz for the absolute value of the phase measured under dry column packing, while a steep rise occurs at high frequencies under wet column packing. The dry column packing data is fitted using a single Cole-Cole model, while the wet column packing data is fitted using a double Cole-Cole model. Substitute the spectral data into the model, and solve for each model parameter using the nonlinear least squares inversion fitting method.

4. The method for determining rare earth content by ion adsorption as described in claim 3, characterized in that, In S5, the calculation process for the normalized charge rate includes: In the double Cole-Cole model, the normalized charge rate is obtained by dividing the charge rate by the zero-frequency resistivity. , The normalized charge rate in the low-frequency Cole-Cole term with a longer relaxation time is used as a parameter to describe the magnitude of the electric double-layer polarization. In the single Cole-Cole model, the normalized charge rate is obtained by dividing the charge rate by the zero-frequency resistivity. ; in, Mn The normalized charge rate is represented by the subscripts 1 and 2, which are used to distinguish the different polarization mechanisms in the double Cole-Cole model.

5. The method for determining rare earth content by ion adsorption as described in claim 4, characterized in that, In S6, the process of establishing a quantitative relationship prediction model includes: A quantitative relationship prediction model between charge rate and total rare earth oxide mass fraction was established by fitting measurement data obtained under wet and dry column packing methods. The expression is as follows: ； in, REO This represents the mass fraction of total rare earth oxides. a , b The model parameters were obtained by performing linear regression on a set of calibration samples with known total rare earth oxide mass fractions. A quantitative predictive model for the relationship between normalized charge rate and total rare earth oxide mass fraction obtained by fitting measurement data under wet-filled column conditions was established, directly correlating rare earth oxide content and electrical parameters under fully saturated conditions. ； in, γ , δ The model parameters are obtained by performing linear regression on a set of calibration samples with known total rare earth oxide mass fractions.

6. The method for determining rare earth content by ion adsorption as described in claim 5, characterized in that, After establishing a quantitative relationship prediction model, the following is also included: S7. Model reliability test: The model reliability test is performed in sequence by testing the model fitting index, cross-validation with leave-one-out method, and comparison method. If all tests pass, the model reliability test is passed. Model fit index verification: Calculate the relative root mean square error of the model fit. The relative root mean square error of the amplitude is less than 4.5% and the relative root mean square error of the phase is less than 15%. If the above indexes are not met, the model is refitted. Comparison method: Sample and use a quantitative relationship prediction model to predict the total rare earth oxide mass fraction. Compare the prediction results with the results of standard chemical analysis methods. If the average relative error is less than 15%, the model is considered to have passed the test; otherwise, the model is refitted.

7. An ion adsorption type rare earth content determination system, characterized in that, For implementing the ion adsorption type rare earth content determination method as described in any one of claims 1-6, the system includes a soil column device, an electrode group, and a full waveform impedance analyzer; The soil column device includes a sample chamber, a bottom water inlet, and a top water outlet, with the bottom water inlet and top water outlet respectively located at the top and bottom of the sample chamber. The electrode assembly includes a power supply electrode and a measuring electrode. The power supply electrode is disposed at the top and bottom of the sample chamber, and the measuring electrode is disposed on the side wall of the sample chamber. The full-waveform impedance analyzer is electrically connected to the electrode group and is used to measure the complex resistivity spectrum of the soil column device within a preset frequency range using the four-electrode method.

8. A computer device, characterized in that, Including memory and processor; The memory is used to store computer programs that can run on the processor; The processor is used to execute the computer program to implement the steps of the ion adsorption type rare earth content determination method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the ion adsorption type rare earth content determination method as described in any one of claims 1 to 6.

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