Ion-type rare earth leaching field residual leaching agent leaching regulation method and system

Abstract

This invention discloses a method and system for controlling the leaching of residual leaching agents in ion-type rare earth leaching fields. A reaction-diffusion coupled kinetic model is established; initial parameters of the physicochemical properties of the tailings soil and the desorption rate constant are obtained; initial leaching conditions are set and substituted into the model to obtain the cation desorption rate of the leaching agent; combined with the leaching flow rate, a curve of cumulative desorption over time is obtained; the inflection point of the cumulative desorption in the curve is identified; and the leaching intensity and leaching method during the leaching process are controlled; the controlled leaching conditions are substituted back into the model to determine the next inflection point of the cumulative desorption in the curve, and this process is repeated until the control termination condition is reached. By using the method and system of this invention, the physicochemical properties of the ore soil are tested, the cation desorption rate of the residual leaching agent is predicted, and then the leaching process is controlled based on the predicted cation desorption rate, thereby improving leaching efficiency and reducing water consumption.

Description

Technical Field

[0001] This invention belongs to the field of ecological restoration and environmental engineering technology of ion-type rare earth mines, specifically involving a method and system for controlling the leaching of residual leaching agents in ion-type rare earth leaching fields. Background Technology

[0002] The in-situ mining process of ion-adsorption rare earth minerals requires the injection of leaching agents into the ore body, resulting in a large amount of leaching agent residues in the ore soil. Under the influence of rainfall infiltration and groundwater disturbance, the residual leaching agent continues to be released into the soil and surrounding waters of the mining area, causing environmental pollution.

[0003] In the mining of ion-adsorption rare earth elements, the method for treating residual leaching agents is to inject top water for rinsing after leaching. However, the rinsing time is based on experience, resulting in poor rinsing effects. This is mainly manifested in the fact that, even years after mine closure, ammonia nitrogen levels in the surrounding waters still exceed standards. An investigation found that 12 years after the closure of a certain mine, the residual ammonium was 40 times the background value of ammonium nitrogen in the original ore soil. To leach the residual leaching agent as quickly as possible, the rinsing operation is often not based on the desorption rate of the residual leaching agent, resulting in excessively high rinsing intensity. This leads to low concentrations of leaching agent in the leachate, increasing the difficulty of leaching agent reuse and increasing water consumption. Furthermore, insufficient rinsing results in large amounts of residual leaching agent, increasing both mining costs and environmental pollution risks.

[0004] The core reason for the poor leaching effect is that the mechanism of desorption of leaching agent from clay mineral surface is not understood, and there is no reliable model to predict the desorption rate of residual leaching agent, so the leaching process cannot be scientifically controlled. Summary of the Invention

[0005] To address the aforementioned deficiencies or improvement needs of existing technologies, this invention proposes a method and system for controlling the leaching of residual leaching agents in ion-type rare earth leaching fields, thereby improving leaching efficiency, reducing water consumption, and lowering mining costs.

[0006] To achieve the above objectives, according to one aspect of the present invention, a method for controlling the leaching of residual leaching agent in an ion-type rare earth leaching field is provided, comprising the following steps: A reaction-diffusion coupled kinetic model was established, consisting of the following equations: the microscopic kinetic equation for the desorption of ore leaching agent cations on the surface of mineral particles regulated by activation energy and electrostatic potential energy; the potential distribution equation described by Gouy-Chapman double layer theory; the non-uniform distribution equation of activation energy at adsorption sites described by Weibull distribution; and the Nernst-Planck equation for mass transfer controlled by diffusion and electromigration. The initial parameters of the physicochemical properties of tailings soil and the desorption rate constant are obtained, the initial leaching conditions are set, and the equations are substituted into the equations to obtain the cationic desorption rate of the leaching agent. The initial parameters of the physicochemical properties of tailings soil include the cationic concentration of the leaching agent on the surface of the soil, the surface charge density, and the specific surface area. Based on the obtained cationic desorption rate of the leaching agent and the rinsing flow rate, the cumulative desorption amount versus time curve is obtained. The inflection point of the cumulative desorption amount in the curve is identified, and the rinsing intensity and rinsing method are controlled during the rinsing process. The adjusted rinsing conditions are substituted back into the equations to solve the problem. The time when the next inflection point of the cumulative desorption in the curve appears under the adjusted rinsing conditions is determined. This process is repeated until the termination condition of the adjustment is met, thus achieving dynamic control of the rinsing process.

[0007] According to the above scheme, the specific surface area is obtained by testing using the BET low-temperature nitrogen adsorption method.

[0008] According to the above scheme, the initial cation concentration and surface charge density of the ore surface leaching agent are obtained through the following methods: The cation exchange capacity of the ore soil was tested using the barium chloride buffer method. A cup leaching experiment was conducted using the same leaching agent concentration and solid-liquid ratio as during the engineering mining process to test the total amount of leaching agent cations adsorbed by the ore soil. The ore soil was then rinsed with water to test the content of leaching agent cations in the rinsed water. Calculate the initial concentration of cations, surface charge density, and surface potential of the leaching agent on the surface of the mineral soil.

[0009] According to the above scheme, the desorption rate constant is obtained through static desorption experiments, specifically as follows: The desorption kinetic curve was determined by static desorption, and the desorption rate constant was obtained by fitting.

[0010] According to the above scheme, the space is discretized using the finite difference method, and the time integration is solved using a variable step size algorithm.

[0011] According to the above scheme, the rinsing intensity during the rinsing process is adjusted, specifically including: Adjust at least one of the following: rinsing fluid flow rate, rinsing fluid velocity, rinsing fluid temperature, and rinsing duration.

[0012] According to the above scheme, the rinsing methods include continuous rinsing and intermittent rinsing.

[0013] According to the above scheme, the termination conditions for regulation are that the leachate concentration reaches the concentration threshold and the desorption rate reaches the rate threshold.

[0014] According to another aspect of the present invention, a residual leaching agent rinsing and control system for ion-type rare earth leaching fields is provided, comprising: The model building module is used to establish a reaction-diffusion coupled kinetic model, which consists of the following equations: the microscopic kinetic equation for the desorption of ore leaching agent cations on the surface of mineral particles controlled by activation energy and electrostatic potential energy; the potential distribution equation described by Gouy-Chapman double layer theory; the non-uniform distribution equation of activation energy of adsorption sites described by Weibull distribution; and the Nernst-Planck equation for mass transfer process controlled by diffusion and electromigration. The model solving module is used to substitute the obtained initial parameters of the physicochemical properties of tailings soil, desorption rate constant, and initial leaching conditions into the equation system to solve for the cationic desorption rate of the leaching agent. The initial parameters of the physicochemical properties of tailings soil include the initial concentration of leaching agent cationic ions on the soil surface, surface charge density, and specific surface area. The control module is used to obtain the cumulative desorption amount versus time curve based on the obtained cation desorption rate of the leaching agent and the rinsing flow rate, find the inflection point of the cumulative desorption amount in the curve, and control the rinsing intensity and rinsing method during the rinsing process. The iterative module is used to substitute the adjusted elution conditions back into the equations for solution, determine the time when the next inflection point of the cumulative desorption in the curve will occur under the adjusted elution conditions, and repeat this process until the termination condition of the adjustment is reached, thereby realizing the dynamic control of the elution process.

[0015] According to the above system, the model solving module uses the finite difference method to discretize the space and uses a variable step size algorithm to solve the time integral problem.

[0016] In summary, compared with the prior art, the above-described technical solutions conceived by this invention can achieve the following beneficial effects: By establishing a reaction-diffusion coupled kinetic model to calculate the desorption rate of leaching agent cations, the desorption process of leaching agent cations from the surface of clay minerals was characterized from a microscopic perspective. The desorption rate of residual leaching agent cations can be predicted simply by testing the physicochemical properties of the ore. Then, the predicted desorption rate of leaching agent cations can be fed back to regulate the leaching process. During the regulation process, the desorption rate of leaching agent cations can be continuously acquired for iterative control, thereby improving leaching efficiency, reducing water consumption, and lowering mining costs. Attached Figure Description

[0017] Figure 1 This is a flowchart of a method provided in an embodiment of the present invention.

[0018] Figure 2 This is a flowchart of a model solving process provided in an embodiment of the present invention.

[0019] Figure 3 This is a rinsing prediction verification diagram provided in an embodiment of the present invention.

[0020] Figure 4 This is a schematic diagram of a static desorption experiment provided in an embodiment of the present invention. Detailed Implementation To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0021] The present invention aims to establish a residual leaching agent leaching control method that combines physical mechanisms and engineering applicability, so as to realize dynamic control of the residual leaching agent leaching process and improve leaching efficiency.

[0022] To achieve the above objectives, according to one aspect of the present invention, this embodiment provides a method for controlling the leaching of residual leaching agent in ion-type rare earth leaching fields, such as... Figure 1 As shown, it includes the following steps: S1. Obtain the initial parameters of the physical and chemical properties of the tailings soil, including the initial concentration Γ0 of the leaching agent on the soil surface, the surface charge density, and the specific surface area.

[0023] The specific surface area of ​​mineral soil was determined using the BET low-temperature nitrogen adsorption method. A The cation exchange capacity (CEC) of the mineral soil was tested using the barium chloride buffer method, in m² / kg, and the surface charge density was determined. σ 0 = (CEC × Z × F ) / A C / m 2 , Z The valence state of the leaching agent cation. F is the Faraday constant. Cup leaching experiments were conducted using the same leaching agent concentration and solid-liquid ratio as during engineering mining to test the total amount of leaching agent cations adsorbed by the ore soil. Q Z , mg / g; Calculate the initial cationic concentration Γ0 of the leaching agent on the surface of the ore soil = Q Z / ( M × A ), mol / m 2 , M Let be the molar mass of the leaching agent cation, in g / mol. Calculate the surface potential. φ 0, V: by ,in , c 0 represents the cation concentration of the leaching agent in the bulk solution. ε Where is the dielectric constant. RThe gas constant is... T For temperature, based on specific surface area A The cation exchange capacity (CEC) can be used to calculate the cation exchange capacity. , will get Substitute: The surface potential can be calculated. φ 0。

[0024] S2. Obtain the desorption rate constant. k 0. Specifically, the change curve of leaching agent cations over time is determined by static desorption, thus obtaining the desorption curve. A schematic diagram of the desorption is shown below. Figure 4 The desorption curve was fitted using the Weber-Morris internal diffusion kinetics model, and the desorption rate constant was calculated based on the fitted equation. k 0.

[0025] S3. Establish a reaction-diffusion coupled kinetic model, consisting of the following equations: the microscopic kinetic equation for the desorption of ore leaching agent cations on the surface of mineral particles regulated by activation energy and electrostatic potential energy; the potential distribution equation described by the Gouy-Chapman double layer theory; the non-uniform distribution equation of activation energy at adsorption sites described by the Weibull distribution; and the Nernst-Planck equation for the mass transfer process controlled by diffusion and electromigration.

[0026] The reaction-diffusion coupled kinetic model systematically characterizes the mass transfer behavior of charged particles under the combined action of concentration gradient and potential gradient, and fully covers the coupling mechanisms of multiple processes such as intrinsic desorption, electrostatic negative feedback, double-layer relaxation, diffusion and electromigration.

[0027] S4. Combine the initial parameters of the physicochemical properties of the tailings soil obtained in S1 with the desorption rate constant obtained in S2. k 0. Set the initial leaching conditions such as temperature and leaching flow rate, and substitute them into the equation system of S3 to solve for the cationic desorption rate of the leaching agent.

[0028] Taking MATLAB numerical solution as an example, the space is discretized using the finite difference method, and the time solution is performed using a variable step-size algorithm. ODE coupling is used to solve for the potential, concentration, and desorption rate. The concentration of leaching agent cations in the desorption solution can be calculated based on the desorption rate, and then the cumulative leaching amount of leaching agent cations can be calculated based on the leaching flow rate. The output is the concentration breakthrough curve of the leaching agent cations in the desorption solution and the cumulative desorption amount versus time curve. The solution process is as follows: Figure 2 As shown.

[0029] S5. Based on the model calculation, obtain the cumulative desorption curve or concentration breakthrough curve of the leaching agent cations to determine the time point when the leaching efficiency decreases, such as the inflection point of the cumulative desorption. Before the inflection point appears, adjust the leaching intensity or leaching method. The control of leaching intensity specifically includes adjusting at least one of the following: leaching solution flow rate, leaching solution velocity, leaching solution temperature, and leaching duration. Leaching methods include continuous leaching and intermittent leaching.

[0030] S6. Substitute the rinsing conditions adjusted in S5 back into the aforementioned equation system for iteration, determine the next inflection point time under these rinsing conditions, and adjust the rinsing intensity or rinsing method again before the inflection point occurs. Repeat this process to achieve dynamic control of the rinsing process. Set the termination conditions for control: the eluent concentration reaches the concentration threshold, and the desorption rate reaches the rate threshold. When the termination conditions are met, stop rinsing.

[0031] According to another aspect of the present invention, this embodiment provides a residual leaching agent control system for ion-type rare earth leaching fields, comprising: The model building module is used to establish a reaction-diffusion coupled kinetic model, which consists of the following equations: the microscopic kinetic equation for the desorption of ore leaching agent cations on the surface of mineral particles controlled by activation energy and electrostatic potential energy; the potential distribution equation described by Gouy-Chapman double layer theory; the non-uniform distribution equation of activation energy of adsorption sites described by Weibull distribution; and the Nernst-Planck equation for mass transfer process controlled by diffusion and electromigration.

[0032] The model solution module is used to substitute the acquired initial parameters of the tailings soil's physicochemical properties, desorption rate constant, and initial leaching conditions into the equation system to obtain the cation desorption rate of the leaching agent; and the initial parameters of the tailings soil's physicochemical properties, including the initial concentration of leaching agent cations on the soil surface, surface charge density, and specific surface area. During the solution process, the finite difference method is used to discretize the space, and a variable step-size algorithm is used for time integration.

[0033] The control module is used to obtain the cumulative desorption amount versus time curve based on the obtained cation desorption rate of the leaching agent and the rinsing flow rate, find the inflection point of the cumulative desorption amount in the curve, and control the rinsing intensity and rinsing method during the rinsing process.

[0034] The iterative module is used to substitute the adjusted elution conditions back into the equations for solution, determining the time when the next inflection point of the cumulative desorption amount in the curve occurs under the adjusted elution conditions. This process is repeated until the termination condition is met, thus achieving dynamic control of the elution process. The termination condition is that the eluent concentration reaches a concentration threshold and the desorption rate reaches a rate threshold.

[0035] The invention will be further illustrated below with specific examples.

[0036] The present invention was applied to tailings washing in an ion-adsorption rare earth mine in southern China. The results of obtaining the physicochemical properties of the ore and soil, the coupled model analysis, the prediction results and the experimental results are compared as follows.

[0037] I. Examples of obtaining physicochemical formation parameters of tailings The average content of cationic A in the residual leaching agent in the ore soil was 0.252 mg / g, the specific surface area of ​​the ore soil was 22960 m² / kg, and the initial concentration Γ0 of cationic A in the leaching agent on the ore soil surface was 6.08 × 10⁻⁶. 7 mol / m 2 The cation exchange capacity (CEC) is 1.469 mmol / kg, and the surface charge density (σ0) is... 0.117C / m 2 The surface potential is 0.118 V. Other relevant initial parameter settings are shown in Table 1.

[0038] Table 1 Initial Values ​​and Constant Settings

[0039] Specific surface area was obtained using the BET low-temperature nitrogen adsorption method. The cation exchange capacity of the ore was tested using the barium chloride buffer method. A cup leaching experiment was conducted using the same leaching agent concentration and solid-liquid ratio as during the mining process to test the total amount of leaching agent cations adsorbed by the ore. The ore was then rinsed with water, and the content of leaching agent cations in the rinse water was measured. The initial concentration of leaching agent cations, surface charge density, and surface potential on the ore surface were calculated. Detailed calculation procedures are omitted.

[0040] The desorption kinetics curve was determined by static desorption, and the desorption rate constant was obtained by fitting. Specific procedures are omitted.

[0041] II. Coupled Model Simulation Analysis (1) Establish the governing equations of the reaction-diffusion coupling model.

[0042] A micro-kinetic model of desorption considering surface reactions was constructed, and its kinetic equation is shown in Equation 1.

[0043] Relation 1:

[0044] In the formula: k des (t) represents the instantaneous desorption rate of leaching agent cation A; k 0 represents the desorption rate constant; β ( tThe electrostatic potential energy is the local increase in the electric double layer caused by the desorption of ammonium ions at their original positions. Its value can be calculated using Equation 2. t For time, R The gas constant is... T For temperature.

[0045] Relation 2:

[0046] In the formula: Z represents the ionic valence state of the cation. F Δ is the Faraday constant. φ ( t ) represents the change in surface potential.

[0047] According to the double-layer theory, the relationship between surface potential and surface ion concentration can be established, as shown in Equation 3.

[0048] Relationship 3:

[0049] In the formula: For the surface of mineral soil t The electric potential at a given moment; ε Where is the dielectric constant. c ( t ) represents the concentration of cations in the leaching agent of the bulk solution; Γ( t )for t The surface concentration of cations in the leaching agent at any given time. Changes in surface concentration further affect the subsequent desorption of ammonium ions, as shown in Equation 4.

[0050] Relation 4:

[0051] Under stable leaching conditions, the amount of leaching solution injected equals the amount that flows out, and the concentration of cations in the leaching agent in the bulk solution is... c ( t ) and instantaneous desorption rate k des The relationship of (t) is shown in relation 5.

[0052] Relation 5:

[0053] in: v Flow rate.

[0054] The concentration of cation A in the diffusion layer decreases continuously with desorption, which in turn causes the surface potential to change continuously. These two factors together control the diffusion of desorbed ions into the bulk solution, and the governing equation is shown in Equation 6.

[0055] Relation 6:

[0056] In relation 6: This represents the change in the concentration of leaching agent cations within the electric double layer over time. x For one-dimensional coordinates, D denoted as α, where α is the diffusion coefficient of the leaching agent cations in the solution.

[0057] According to the double-layer theory, the relationship between the ion concentration in the diffuse layer and the ion concentration in the bulk solution is shown in Equation 7.

[0058] Relation 7:

[0059] (2) Substitute the obtained relevant parameters and initial values ​​into the reaction-diffusion coupling control equation set, perform numerical calculations, obtain the concentration breakthrough curve of leaching agent cation desorption, multiply the concentration of the leaching solution by the volume of the leaching solution (which can be calculated according to the leaching flow rate) to calculate the cumulative desorption amount, and output the cumulative desorption amount-time change curve.

[0060] III. Comparison between Predicted Results and Eluting Results The prediction results and rinsing results are shown in the figure. Figure 3 As shown in the figure, the predicted results and the elution results show the same trend: a rapid increase followed by a gradual plateau, with the inflection point times being basically the same. The relative error of the simulated maximum desorption rate is 5.6%. The high degree of agreement between the predicted curve and the elution curve indicates that the coupled model has a good effect on predicting the desorption rate.

[0061] IV. Rinse Control Based on the prediction results of the desorption rate of the coupled model, when the leaching time is about 30 minutes, the increase in desorption slows down and the concentration of the leachate decreases. Therefore, the leaching intensity is reduced at about 25 minutes. The new leaching intensity, residual leaching agent and other parameters are substituted into the model to recalculate the desorption rate. The leaching conditions are adjusted again based on the prediction results. This cycle is repeated until the concentration of the leachate is lower than a certain preset concentration threshold, at which point the leaching is stopped.

[0062] This invention calculates the desorption rate of leaching agent by establishing a reaction-diffusion coupled kinetic model, realizing dynamic prediction of the desorption rate of residual leaching agent. Based on the prediction of the desorption rate, the leaching process is dynamically controlled to improve leaching efficiency, reuse leaching ore, reduce water consumption, lower mining costs, and ensure that the environmental impact of residual leaching agent after leaching is controllable.

[0063] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0064] It should be noted that, depending on the implementation needs, the various steps / components described in this application can be broken down into more steps / components, or two or more steps / components or parts of the operation of steps / components can be combined into new steps / components to achieve the purpose of this invention.

[0065] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for leaching control of ion-type rare earth residual in-situ leaching reagent, characterized in that: Includes the following steps: ​ A reaction-diffusion coupled kinetic model was established, consisting of the following equations: the microscopic kinetic equation for the desorption of ore leaching agent cations on the surface of mineral particles regulated by activation energy and electrostatic potential energy; the potential distribution equation described by Gouy-Chapman double layer theory; the non-uniform distribution equation of activation energy at adsorption sites described by Weibull distribution; and the Nernst-Planck equation for mass transfer controlled by diffusion and electromigration. The initial parameters of the physicochemical properties of tailings soil and the desorption rate constant are obtained, the initial leaching conditions are set, and the equations are substituted into the equations to obtain the desorption rate of the leaching agent cations. The initial parameters of the physicochemical properties of tailings soil include the initial concentration of leaching agent cations on the soil surface, the surface charge density, and the specific surface area. Based on the obtained cationic desorption rate of the leaching agent and the rinsing flow rate, the cumulative desorption amount versus time curve is obtained. The inflection point of the cumulative desorption amount in the curve is identified, and the rinsing intensity and rinsing method are controlled during the rinsing process. The adjusted rinsing conditions are substituted back into the equations to solve the problem. The time when the next inflection point of the cumulative desorption in the curve appears under the adjusted rinsing conditions is determined. This process is repeated until the termination condition of the adjustment is met, thus achieving dynamic control of the rinsing process.

2. The method for in-situ leaching control of ion-type rare earth in-situ leaching residual ore agent according to claim 1, characterized in that: The specific surface area was obtained by testing using the BET low-temperature nitrogen adsorption method.

3. The method of claim 1, wherein the method is characterized by: The initial cation concentration and surface charge density of the ore surface leaching agent were obtained through the following methods: The cation exchange capacity of the ore soil was tested using the barium chloride buffer method. A cup leaching experiment was conducted using the same leaching agent concentration and solid-liquid ratio as during the engineering mining process to test the total amount of leaching agent cations adsorbed by the ore soil. The ore soil was then rinsed with water to test the content of leaching agent cations in the rinsed water. Calculate the initial concentration of cations, surface charge density, and surface potential of the leaching agent on the surface of the mineral soil.

4. The method of claim 1, wherein the method is characterized by: The desorption rate constant was obtained through static desorption experiments, specifically: The desorption kinetic curve was determined by static desorption, and the desorption rate constant was obtained by fitting.

5. The method of claim 1, wherein the method is characterized by: In solving the problem, the finite difference method is used to discretize the space, and a variable step size algorithm is used for time integration.

6. The method of claim 1, wherein the method is characterized by: Controlling the rinsing intensity during the rinsing process specifically includes: Adjust at least one of the following: rinsing fluid flow rate, rinsing fluid velocity, rinsing fluid temperature, and rinsing duration.

7. The method of claim 1, wherein the method is characterized by: The rinsing methods include continuous rinsing and intermittent rinsing.

8. The method of claim 1, wherein the method is characterized by: The control is terminated when the leachate concentration reaches the concentration threshold and the desorption rate reaches the rate threshold.

9. The ion-type rare earth leaching mine residual leaching agent leaching control system, characterized in that: include: The model building module is used to establish a reaction-diffusion coupled kinetic model, which consists of the following equations: the microscopic kinetic equation for the desorption of ore leaching agent cations on the surface of mineral particles controlled by activation energy and electrostatic potential energy; the potential distribution equation described by Gouy-Chapman double layer theory; the non-uniform distribution equation of activation energy of adsorption sites described by Weibull distribution; and the Nernst-Planck equation for mass transfer process controlled by diffusion and electromigration. The model solving module is used to substitute the obtained initial parameters of the physicochemical properties of tailings soil, desorption rate constant, and initial leaching conditions into the equation system to solve for the cationic desorption rate of the leaching agent. The initial parameters of the physicochemical properties of tailings soil include the initial concentration of leaching agent cationic ions on the soil surface, surface charge density, and specific surface area. The control module is used to obtain the cumulative desorption amount versus time curve based on the obtained cation desorption rate of the leaching agent and the rinsing flow rate, find the inflection point of the cumulative desorption amount in the curve, and control the rinsing intensity and rinsing method during the rinsing process. The iterative module is used to substitute the adjusted elution conditions back into the equations for solution, determine the time when the next inflection point of the cumulative desorption in the curve will occur under the adjusted elution conditions, and repeat this process until the termination condition of the adjustment is reached, thereby realizing the dynamic control of the elution process.

10. The residual leaching agent rinsing and control system for ion-type rare earth leaching fields according to claim 9, characterized in that: The model solving module uses the finite difference method to discretize the space and a variable step size algorithm to solve the time integral problem.

Images