A method of predicting structural stability and lithium ion adsorption selectivity of modified aluminum-based lithium adsorbents
By using DFT simulation calculations to predict the structural stability and lithium-ion adsorption selectivity of modified aluminum-based lithium adsorbents, the problems of poor cycle stability and low selectivity of aluminum-based lithium adsorbents are solved, enabling efficient screening and modification, reducing costs and improving performance.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- TIANJIN UNIV OF SCI & TECH
- Filing Date
- 2024-01-08
- Publication Date
- 2026-06-16
AI Technical Summary
Aluminum-based lithium adsorbents suffer from poor cycle stability and low lithium-ion adsorption selectivity, while existing experimental testing methods are costly and inefficient.
DFT simulation was used to predict the structural stability and lithium-ion adsorption selectivity of modified aluminum-based lithium adsorbents. By establishing modified and unmodified models, geometric configuration optimization and frequency verification were performed. Binding energy and cavity radius of adsorption sites were calculated to screen out highly efficient modified adsorbents.
This study achieved efficient screening of aluminum-based lithium adsorbents, reduced experimental costs, improved the stability and lithium-ion selectivity of the adsorbents, and the experimental results were in good agreement with the theoretical results.
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Abstract
Description
Technical Field
[0001] This invention relates to the field of aluminum-based lithium adsorbents, and particularly to a method for predicting the structural stability and lithium-ion adsorption selectivity of modified aluminum-based lithium adsorbents. Background Technology
[0002] The dual carbon goals of "peak carbon by 2030 and carbon neutrality by 2060" demonstrate my country's determination to actively address global climate change. The proposal of these dual carbon goals marks a new stage in the development of my country's new energy vehicle industry. The rapid development of new energy vehicles has greatly boosted the demand for lithium products. Lithium extraction from salt lake brine, due to its reserves and cost advantages, can safeguard the development of China's new energy vehicle industry. Lithium adsorbents are the core of the adsorption method for lithium extraction from salt lake brine. Currently, the main adsorbents include manganese-based lithium ion sieves, titanium-based lithium ion sieves, and aluminum-based lithium adsorbents. Among them, aluminum-based lithium adsorbents have advantages such as simple synthesis methods, high lithium ion selectivity, and high Li... + Desorption can be achieved simply by washing with water, making it one of the most promising adsorbents currently available.
[0003] The poor cycle stability of aluminum-based lithium adsorbents is a recognized bottleneck problem in the industry. During repeated adsorption and desorption processes, the adsorption capacity continuously decreases, and the short replacement cycle of the adsorbent is a significant factor contributing to the high operating cost of lithium extraction via adsorption. Furthermore, lithium-ion adsorption selectivity is also an important indicator that needs attention. Currently, methods to improve the stability and lithium-ion adsorption selectivity of aluminum-based lithium adsorbents mainly rely on experimental testing, which has drawbacks such as long experimental cycles, high costs, and a lack of rigor.
[0004] To address the above problems, this invention is proposed. Summary of the Invention
[0005] To address the aforementioned technical problems, this invention provides a novel method for predicting the structural stability and lithium-ion adsorption selectivity of modified aluminum-based lithium adsorbents using DFT (Density Functional Theory) simulations. This invention achieves precise control over the bulk layers of the aluminum-based lithium adsorbent through DFT simulations; it can accurately calculate the binding energy of molecular clusters and the cavity radius of adsorption sites, thereby predicting the structural stability and lithium-ion adsorption selectivity of the modified adsorbent. Furthermore, this invention verifies the accuracy of the predictions through experiments, achieving a good match between theoretical and experimental results. This invention leverages the advantages of DFT simulations to efficiently screen aluminum-based lithium adsorbents for structural modification, providing theoretical guidance for the modification of aluminum-based lithium adsorbents.
[0006] The technical solution of the present invention to solve the above problems is as follows:
[0007] This invention provides a method for predicting the structural stability and lithium-ion adsorption selectivity of a modified aluminum-based lithium adsorbent, wherein the modified aluminum-based lithium adsorbent is a cationic modified aluminum-based lithium adsorbent, and the prediction method includes the following steps:
[0008] (1) Establish the main plate structure of the modified aluminum-based lithium adsorbent and the main plate structure of the unmodified aluminum-based lithium adsorbent, namely the modified model and the unmodified model.
[0009] (2) Perform geometric configuration optimization and frequency verification on the modified and unmodified models;
[0010] (3) Calculate and compare the binding energy of the modified model and the unmodified model;
[0011] When the binding energy of the modified model is greater than that of the unmodified model, the structural stability of the modified aluminum-based lithium adsorbent is improved; when the binding energy of the modified model is less than that of the unmodified model, the structural stability of the modified aluminum-based lithium adsorbent is reduced; when the binding energy of the modified model is equal to that of the unmodified model, the structural stability of the modified aluminum-based lithium adsorbent remains unchanged.
[0012] (4) Calculate and compare the cavity radius of the adsorption sites in the modified model and the unmodified model;
[0013] When the adsorption site cavity radius of the modified model is larger than that of the unmodified model, the lithium-ion adsorption selectivity of the modified aluminum-based lithium adsorbent decreases; when the adsorption site cavity radius of the modified model is smaller than that of the unmodified model, the lithium-ion adsorption selectivity of the modified aluminum-based lithium adsorbent increases; when the adsorption site cavity radius of the modified model is equal to that of the unmodified model, the lithium-ion adsorption selectivity of the modified aluminum-based lithium adsorbent remains unchanged.
[0014] Preferably, the cation includes, but is not limited to: Be 2+ Na + Mg 2+ K + Ca 2+ ,Sc 3+ Ti 3+ V 4+ Cr 3+ Mn 3 + Co 3+ Ni 3+ Cu 3+ Zn 2+ Ga 3+ 、Ge 4+ 、Ge 2+ Fe 3+ .
[0015] Preferably, in step (2), in order to verify the reliability of the computational model, the basic unit [AlO6] constituting the computational model is tested respectively. i+Configuration optimization and frequency calculations were performed. The bond lengths and bond angles of the optimized clusters after different cation modifications need to be calculated.
[0016] Specifically, a DFT-based simulation method was adopted, using the hybrid functional PBE0 and basis set 6-31G(d), and DFT-D3(BJ) dispersion correction was performed to optimize the geometric configuration and verify the frequency of the modified and unmodified models.
[0017] Preferably, in step (3), in order to compare the stability of aluminum-based lithium adsorbents modified by different ions, it is necessary to calculate the energy of the ground-state particles constituting the clusters and the ground-state energy after optimization of the configuration of the different cation-modified clusters. Based on the calculated energy values, the binding energy of the clusters after modification by different cations is calculated. The binding energy of clusters of the same size represents the relative stability of the clusters. The larger the binding energy, the stronger the stability of the cluster. By comparing with the unmodified model, the structural stability of the modified system is predicted. If the binding energy of the modified model is greater than that of the unmodified model, it means that the structural stability of the modified aluminum-based lithium adsorbent has increased; if the binding energy of the modified model is less than that of the unmodified model, it means that the structural stability of the modified aluminum-based lithium adsorbent has decreased.
[0018] Specifically, the combination energy of the modified and unmodified models can be calculated through the following steps:
[0019] (31) Calculate the ground state energy of all ions that make up the model;
[0020] (32) Calculate the energy of the molecular cluster after configuration optimization;
[0021] (33) Calculate the binding energy of the model according to equation (1):
[0022] ΔE=∑E ion -E cluster Equation (1)
[0023] Where ΔE is the binding energy of the molecular cluster, au; E ion It is the ground-state energy of all the ions that make up the cluster, au; E cluster It is the calculated energy after molecular cluster configuration optimization, au.
[0024] Preferably, in step (4), the calculated cavity radius of the adsorption sites before and after modification is used to determine the lithium-ion adsorption selectivity of the modified aluminum-based lithium adsorbent. If the cavity radius of the adsorption sites in the modified model is larger than that in the unmodified model, it indicates that the lithium-ion adsorption selectivity of the modified aluminum-based lithium adsorbent is reduced; if the cavity radius of the adsorption sites in the modified model is comparable to that in the unmodified model, it indicates that the modified aluminum-based lithium adsorbent still maintains good lithium-ion adsorption selectivity.
[0025] Specifically, the adsorption site cavity radius of the modified and unmodified models is obtained by calculating the Li-O bond length. The adsorption site cavity radius of the modified and unmodified models is equal to the Li-O bond length. Since lithium ions form an octahedral configuration after adsorption, with the lithium ion located at the center of the octahedron and the hydroxyl ion located at the vertices, the Li-O bond length is equal to the cavity radius of the adsorption site.
[0026] The model establishment and reliability verification process in this invention is as follows:
[0027] Let [Al] be formed n (OH2) 2n+4 (OH) 2n-2 ] (n+2)+ The reactions of (n=1-7) clusters are shown in Equations 1 and 2 below, and their binding energy is calculated according to Equation 3:
[0028] 2[Al(OH2)6] 3+ +2OH - =[Al2(OH2)8(OH)2] 4+ +4H2O formula (1)
[0029] [Al n-1 (OH2) 2n+2 (OH) 2n-4 ] (n+1)+ +[Al(OH2)6] 3+ +2OH - =[Al n (OH2) 2n+4 (OH) 2n-2 ] (n+2)+ +5H2O Equation (2)
[0030]
[0031] Where ΔE is the binding energy of the cluster, and au represents the relative stability of the computational system; It is the ground state Al 3+ The calculated energy, au; It is the calculated energy after H2O configuration optimization, au; This is the calculated energy after OH- configuration optimization, au; It is the computational energy after optimizing the cluster configuration, au.
[0032] The present invention has the following beneficial effects:
[0033] This invention establishes a DFT calculation model for the main layer structure of a cationic modified aluminum-based lithium adsorbent. By calculating and comparing the binding energy of the modified molecular clusters and the cavity radius of the adsorption sites in the modified model, the structural stability and adsorption selectivity of the modified aluminum-based lithium adsorbent are predicted. This allows for the screening of cationic modified adsorbents with high adsorption selectivity and stability, solving the problems of time-consuming, labor-intensive, and costly experimental screening. This invention enables advance simulation calculations during the screening process of cationic modified aluminum-based lithium adsorbents.
[0034] Furthermore, this invention verifies the accuracy of the prediction through experiments, achieving a match between theoretical and experimental results.
[0035] This invention utilizes DFT to precisely control the main layers of aluminum-based lithium adsorbents, designs structural models of aluminum-based lithium adsorbents with different cation-modified layers, and verifies their reliability, calculates bond lengths and bond angles, calculates binding energy, and calculates and analyzes the cavity radius of adsorption sites. This enables efficient screening of aluminum-based lithium adsorbents and provides a new method for the modification of aluminum-based lithium adsorbents. Attached Figure Description
[0036] Figure 1 Structural optimization models for different cation-modified clusters;
[0037] Figure 2 The binding energy of different cation-modified clusters;
[0038] Figure 3 The cavity radius of the adsorption sites of different cation-modified clusters;
[0039] Figure 4 Relationship between adsorption capacity of adsorbent before and after iron ion modification and the number of cycles. Detailed Implementation
[0040] The invention will be further described below with reference to the embodiments.
[0041] This specific embodiment is merely an explanation of the present invention and is not intended to limit the present invention. Any changes made by those skilled in the art after reading the specification of the present invention, as long as they are within the scope of the claims, will be protected by patent law.
[0042] Examples of the present invention are based on Be 2+ Na + Mg 2+ K + Ca 2+ ,Sc 3+ Ti 3+ V 2+ V 4+ Cr 3+ Mn3+ Co 3+ Ni 3+ Cu 3 + Zn 2+ Ga 3+ 、Ge 4+ 、Ge 2+ Fe 3+ The calculations are performed for cationic modification. The specific process is shown below.
[0043] S1. Model Establishment
[0044] Model building: Be 2+ Na + Mg 2+ K + Ca 2+ ,Sc 3+ Ti 3+ V 2+ V 4+ Cr 3+ Mn 3+ Co 3+ Ni 3+ Cu 3+ Zn 2+ Ga 3+ 、Ge 4+ 、Ge 2+ Fe 3+ As a modified cation, a computational molecular cluster model was established using computer software.
[0045] S2. Geometry of the modified molecular cluster
[0046] Configuration optimization: The model was optimized and its frequency was verified by using a DFT-based simulation method, selecting hybrid functional PBE0 and basis set 6-31G(d), and performing DFT-D3(BJ) dispersion correction.
[0047] Based on the above models, it can be observed that Li-Al-Be-Cl LDH, Li-Al-Na-Cl LDH, Li-Al-Ca-ClLDH, Li-Al-Zn-Cl LDH, Li-Al-K-Cl LDH, and Li-Al-Ge ( 4+ )-Cl LDH, Li-Al-Ge( 2+ Regardless of whether it's the six-membered ring composed of metal ions or the cavity shape of the lithium ion adsorption site in the )-Cl LDH, the shape of both undergoes varying degrees of deformation, especially in Li-Al-Na-Cl LDH, Li-Al-K-Cl LDH, and Li-Al-Ge(4+)-Cl LDH, indicating that Be 2+ Ca2+ Zn 2 + Na + K + 、Ge 4+ 、Ge 2+ Partial Al in isomorphous substituted adsorbents 3+ At that time, compounds with regular shapes and stable properties cannot be formed.
[0048] Table 1. Average interatomic distance and bond angle after optimization for different cation-modified clusters.
[0049]
[0050] Table 1 lists the bond lengths and bond angles of different cation-modified clusters after structural optimization, including the bond lengths of Al-O, Li-O, and different modified ions (XO), as well as the bond angles of O-Al-O, O-Li-O, and OXO. For the modified adsorbent model capable of forming stable clusters, the bond angles of O-Al-O, O-Li-O, and OXO are approximately 90°. The bond length of Al-O is approximately... The bond lengths of Li-O and various modified XO ions are related to the properties of the ions, and are influenced by the radius of the bare ion and the valence state of the metal ion. As the radius of the bare ion increases, the bond length of Li-O also increases, while as the charge of the metal ion increases, the bond length of Li-O decreases. The bond length variation of XO follows the same pattern as that of Li-O.
[0051] S3. Binding energy calculation of modified molecular clusters
[0052] To compare the stability of aluminum-based lithium adsorbents modified with different ions, the binding energy of the clusters needs to be calculated. The binding energy of clusters of the same size represents their relative stability; the higher the binding energy, the stronger the cluster's stability. To compare the stability of aluminum-based lithium adsorbents modified with different ions, the energies of the ground-state particles constituting the clusters and the ground-state energies after optimization of the configurations of different cation-modified clusters were calculated, as shown in Tables 2 and 3.
[0053] Table 2 Energy after optimization of different particle configurations
[0054]
[0055] Table 3 Energy after optimization of different cation-modified cluster model configurations
[0056]
[0057] Based on the data in Tables 2 and 3, the binding energies of the systems after different cation modifications were calculated. Figure 2, it can be seen that the order of the binding energy from small to large before and after the modification of the adsorbent is: Li-Al-Ca-Cl LDH < Li-Al-Mg-Cl LDH < Li-Al-Zn-Cl LDH < Li-Al-Ge( 2+ )-Cl LDH < Li-Al-V( 2+ )-Cl LDH < Li-Al-Be-Cl LDH < Li-Al-Sc-Cl LDH < Li-Al-Ti-Cl LDH < Li-Al-Cl LDH < Li-Al-Ga-Cl LDH < Li-Al-Mn-Cl LDH < Li-Al-Ni-Cl LDH < Li-Al-Fe-Cl LDH < Li-Al-Co-Cl LDH < Li-Al-Cu-Cl LDH < Li-Al-V( 4+ )-Cl LDH < Li-Al-Cr-Cl LDH. It shows that the stability of the Ca 2+ , Mg 2+ , Zn 2+ , V 2+ , Be 2+ , Sc 3+ , Ti 3+ modified aluminum-based lithium adsorbent decreases, while the stability of the Ga 3+ , Mn 3+ , Ni 3+ , Fe 3+ , Co 3+ , Cu 3+ , V 4+ , Cr 3+ modified aluminum-based lithium adsorbent increases.
[0058] S4. Cavity radius of the adsorption site of the modified model
[0059] The size of the cavity radius of the adsorption site has an important impact on the adsorption selectivity of the adsorbent. To ensure that the adsorbent has high adsorption selectivity for lithium ions in brine, the cavity radius of the adsorption site after modification with different cations needs to be basically the same as that before modification. Figure 3 shows the size of the cavity radius of the adsorption site after modification with different cations. It can be seen that after the modification with Ca 2+ , the cavity radius of the adsorption site is as high as , which is very likely to seriously reduce the adsorption selectivity of the adsorbent. In contrast to Ca 2+ , after the modification with Be 2+ ions, the cavity radius of the adsorption site of the aluminum-based lithium adsorbent is only or so, which will make it difficult for all ions to enter the adsorption site, thus losing the adsorption ability for lithium ions. After the modification with Ga 3+ , Mn 3+ , Ni 3+Fe 3+ Co 3+ Cu 3+ Cr 3+ 、Ge 2+ V 4+ The size of the cavity radius of the adsorption sites after modification is not significantly different from that before modification, which ensures the high lithium-ion adsorption selectivity of the modified aluminum-based lithium adsorbent.
[0060] S5.Fe 3+ Experimental verification of doping modification
[0061] An iron-modified aluminum-based lithium adsorbent was synthesized using lithium chloride, ferric chloride, aluminum chloride, and sodium hydroxide as raw materials. Its lithium-ion adsorption selectivity and stability were tested to verify the accuracy of the DFT screening. The preparation method is as follows:
[0062] Mixture A was prepared by mixing 50 mL of 1.50 mol / L AlCl3 solution and 50 mL of 1.20 mol / L LiCl solution in a stirred tank at 75 °C. Mixture B was prepared by adding 10 mL of 1.0 mol / L FeCl3 solution to mixture A. Mixture B was then prepared by adding 5.00 mol / L NaOH solution dropwise to mixture B at a constant rate of 3 mL / min using a peristaltic pump, controlling the final pH of the reaction to be 6.5. Finally, the mixture was washed with water, centrifuged, and dried to obtain the Fe-modified aluminum-based lithium adsorbent Li-Al-Fe LDH.
[0063] The testing steps are as follows:
[0064] (1) The Li-Al-Fe LDH aluminum-based lithium adsorbent was placed in deionized water for desorption, generating lithium ion adsorption vacancies.
[0065] (2) The aluminum-based lithium adsorbent after desorption in step (1) is placed in the brine to adsorb lithium ions, and the adsorption capacity and adsorption selectivity are calculated according to formula (1) and formula (2), respectively.
[0066]
[0067] In the formula, Q at The adsorption amount at time t, in mg / g; C at Let Li be at time t + The concentration of Li in the initial solution is mg / L; C0 is the initial concentration of Li in the initial solution. + The concentration of is mg / L; V is the volume of the adsorption solution, L;
[0068]
[0069] In the formula, K d C represents the partition coefficient of each metal cation; C0 is the initial concentration, mg / L; C eThe concentration after adsorption equilibrium is mg / L; m is the adsorbent mass in g; V is the solution volume in L.
[0070] (3) The adsorbent was subjected to 30 desorption-adsorption cycles to test its adsorption stability.
[0071] Table 4 Adsorption selectivity of iron-modified adsorbents
[0072]
[0073] Test results are shown in Table 4. It can be seen that K... d (Li + The concentration of Li ions is much higher than that of other metal ions, indicating that the adsorbent has a high affinity for Li ions. + It exhibits excellent selectivity. The selectivity order of Li-Al-Fe-Cl LDH for each ion is as follows: Li + >>Mg 2+ Na + >K + >Ca 2+ .
[0074] It can be noted that after 30 adsorption-desorption cycles, the lithium-ion adsorption capacity of the Li-Al-Cl LDH system decreased from 10.5 mg / g to 7.5 mg / g. The lithium-ion adsorption capacity of the Li-Al-Fe-Cl-10% LDH system decreased from 11.3 mg / g to 11.0 mg / g, a decrease of only 2.5%, far lower than the 28.5% decrease of the Li-Al-Cl LDH system. Clearly, Fe... 3+ The reusability and stability of the doped system are significantly higher than those of the unmodified system, which further verifies the accuracy of the DFT theoretical calculation results from an experimental perspective.
[0075] The present invention has been described above by way of example. It should be noted that any simple modifications, alterations or other equivalent substitutions that can be made by those skilled in the art without creative effort without departing from the core of the present invention fall within the protection scope of the present invention.
Claims
1. A method of predicting structural stability and lithium ion adsorption selectivity of a modified aluminum-based lithium adsorbent, characterized by, The modified aluminum-based lithium adsorbent is a cationic modified aluminum-based lithium adsorbent, and the prediction method includes the following steps: (1) Establish the main plate structure of the modified aluminum-based lithium adsorbent and the main plate structure of the unmodified aluminum-based lithium adsorbent, namely the modified model and the unmodified model. (2) Perform geometric configuration optimization and frequency verification on the modified and unmodified models; (3) Calculate and compare the binding energy of the modified model and the unmodified model; When the binding energy of the modified model is greater than that of the unmodified model, the structural stability of the modified aluminum-based lithium adsorbent is improved; when the binding energy of the modified model is less than that of the unmodified model, the structural stability of the modified aluminum-based lithium adsorbent is reduced; when the binding energy of the modified model is equal to that of the unmodified model, the structural stability of the modified aluminum-based lithium adsorbent remains unchanged. (4) Calculate and compare the cavity radius of the adsorption sites in the modified model and the unmodified model; When the adsorption site cavity radius of the modified model is larger than that of the unmodified model, the lithium-ion adsorption selectivity of the modified aluminum-based lithium adsorbent decreases; when the adsorption site cavity radius of the modified model is smaller than that of the unmodified model, the lithium-ion adsorption selectivity of the modified aluminum-based lithium adsorbent increases; when the adsorption site cavity radius of the modified model is equal to that of the unmodified model, the lithium-ion adsorption selectivity of the modified aluminum-based lithium adsorbent remains unchanged.
2. The method according to claim 1, characterized in that, In step (1), the cations include: Be 2+ , Na + , Mg 2 + , K + , Ca 2+ , Sc 3+ , Ti 3+ , V 4+ , Cr 3+ , Mn 3+ , Co 3+ , Ni 3+ , Cu 3+ , Zn 2+ , Ga 3+ , Ge 4+ , Ge 2+ , Fe 3+ .
3. In the geometric configuration optimization of the model according to claim 1, the characteristic is that, In step (2), a DFT-based simulation method is used, with hybrid functional PBE0 and basis set 6-31G(d) selected, and DFT-D3(BJ) dispersion correction is performed to optimize the geometric configuration and verify the frequency of the modified and unmodified models.
4. The method according to claim 1, characterized in that, In step (3), the binding energy between the modified model and the unmodified model is calculated through the following steps: (31) Calculate the ground state energy of all ions that make up the model; (32) Calculate the energy of the molecular cluster configuration after optimization; (33) Calculate the binding energy of the model according to equation (1): ΔE = ∑E ion -E cluster Equation (1) wherein, DE is the binding energy of the molecular cluster, a.u; E ion is the ground state energy of all ions that make up the cluster, a.u; E cluster is the calculated energy after optimization of the molecular cluster configuration, a.u.
5. The method according to claim 1, characterized in that, In step (4), the cavity radius of the adsorption site in the modified model and the unmodified model is equal to the bond length of the Li-O bond.