A method and system for screening compound agglomerants based on molecular dynamics
By employing a molecular dynamics-based method for screening compound agglomerates, fine particulate matter and solution models are constructed for molecular dynamics calculations. This approach solves the problems of long screening cycles and high costs in existing agglomerate screening technologies, and achieves efficient and accurate agglomerate screening and performance prediction.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2023-04-20
- Publication Date
- 2026-04-03
AI Technical Summary
Existing chemical agglomeration technologies suffer from long implementation cycles and high costs when screening agglomerating agents, and traditional experimental research methods are highly unpredictable, making it difficult to efficiently screen suitable materials.
A molecular dynamics-based screening method for compound agglomerators was adopted. By constructing a fine particulate matter surface model, an agglomerator molecular model, and a solution model, molecular dynamics calculations were performed to screen out highly efficient agglomerators.
It reduces experimental costs, shortens the R&D cycle, improves the accuracy and efficiency of agglomerant screening, and enables the prediction of agglomerant performance.
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Figure CN116453606B_ABST
Abstract
Description
Technical Field
[0001] This application belongs to the field of dust removal technology, specifically relating to a method and system for screening compound agglomerants based on molecular dynamics. Background Technology
[0002] Coal combustion in furnaces produces a large amount of fly ash and fine particulate matter, which enters the atmosphere through chimneys and pollutes the environment. Coal-fired power plants are considered one of the major sources of fly ash and fine particulate matter in the atmosphere. Electrostatic precipitators, as the main dust removal unit in coal-fired power plants, have a dust removal efficiency of over 99.5% for fly ash particles. However, due to the "Greenfield gap" effect of small particles, a large amount of fine particulate matter cannot be captured and is released into the atmosphere.
[0003] Chemical agglomeration technology is a method of capturing fine particulate matter using various adsorbents. By injecting agglomerating agents into flue gas, the fine particulate matter reacts with the agglomerating agents in a physical and chemical manner, causing the fine particles to agglomerate and grow larger, thereby improving the removal efficiency of fine particles.
[0004] Chemical agglomeration requires extensive pre-screening of agglomerating agents when targeting particulate matter with different properties. Industrial applications face practical problems such as long implementation cycles and high costs. Traditional experimental research methods are highly unpredictable due to the complexity of the objects. In recent years, with the development of quantum chemistry, statistical mechanics, computational methods, and the unprecedented improvement in computing power, theoretical calculations have come into focus. In the past, experiments often required a significant amount of time for trial and error to find suitable materials. However, existing theoretical calculation software can effectively reduce the time cost of trial and error and predict the performance of agglomerating agents. Currently, commonly used theoretical calculation software includes Gaussian, VASP, and Materials Studio. Among them, Materials Studio, due to its expertise in calculating macromolecular systems, is suitable for simulating the adsorption of agglomerating agents on fine particulate matter. Summary of the Invention
[0005] This application aims to address the shortcomings of existing technologies by proposing a molecular dynamics-based method and system for screening compound agglomerants. This method facilitates convenient and accurate screening of agglomerants, reduces experimental costs for predicting agglomerant performance, and shortens the research and development cycle.
[0006] To achieve the above objectives, this application provides the following solution:
[0007] A molecular dynamics-based method for screening compound agglomerants includes the following steps:
[0008] Construct a surface model of fine particles;
[0009] A molecular model of an agglomerator was constructed, and the structure of the agglomerator molecular model was optimized to obtain an optimized molecular model.
[0010] Based on the optimized molecular model, a solution model is constructed;
[0011] Molecular dynamics calculations were performed based on the fine particulate surface model and the solution model to obtain the agglomerator binding energy, and screening was completed based on the agglomerator binding energy.
[0012] Preferably, the method for constructing the fine particulate matter surface model includes:
[0013] By performing a unit cell cutting operation on the fine particulate matter, a two-dimensional structure of the fine particulate matter is obtained;
[0014] A vacuum layer of predetermined thickness is added to the two-dimensional structure of the fine particulate matter to obtain a three-dimensional unit cell of the fine particulate matter.
[0015] By fixing the lower-layer atoms of the three-dimensional unit cell of the fine particles, a surface model of the fine particles is obtained.
[0016] Preferably, the method for constructing the agglomerator molecular model includes: setting the degree of polymerization, the number of molecular chains, and the polymer type; constructing a PAM molecular model, an SDBS ion model, and a water molecule model; and combining the PAM molecular model and the SDBS ion model to obtain the agglomerator molecular model.
[0017] Preferably, the method for structure optimization includes: optimizing the agglomerator molecular model based on the FORCITE module to obtain the configuration with the lowest energy, i.e., the optimized molecular model.
[0018] Preferably, the solution model includes: a compound solution model and a PAM solution model;
[0019] The method for constructing the complex solution model includes: constructing the complex solution model based on 5 PAM molecule models, 5 SDBS ion models and 500 water molecule models;
[0020] The method for constructing the PAM solution model includes: constructing the PAM solution model based on 5 PAM molecule models and 500 water molecule models.
[0021] Preferably, the method for calculating the binding energy of the agglomerating agent includes:
[0022] The fine particulate matter surface model and the solution model are combined to obtain the overall configuration, and the overall single-point energy of the overall configuration is calculated.
[0023] The surface model of the fine particulate matter is set as Set A, and the solution model is set as Set B;
[0024] Based on the overall configuration, Set A is deleted to obtain the first configuration, and the first single-point energy of the first configuration is calculated;
[0025] Based on the overall configuration, Set B is deleted to obtain a second configuration, and the second single-point energy of the second configuration is calculated;
[0026] The agglomerant binding energy is calculated based on the overall single-point energy, the first single-point energy, and the second single-point energy.
[0027] Preferably, the formula for calculating the binding energy of the agglomerant is as follows:
[0028] ΔE=E total -E surface -E molecule
[0029] Where ΔE represents the agglomerant binding energy, E total E represents the total single-point energy. surface E represents the second single-point energy. molecule This indicates the first single-point energy.
[0030] This application also provides a molecular dynamics-based system for screening compound agglomerants, including: a surface model construction subsystem, a model optimization subsystem, a solution model construction subsystem, and a kinetic calculation subsystem;
[0031] The surface model construction subsystem is used to construct a surface model of fine particles;
[0032] The model optimization subsystem is used to construct a molecular model of agglomerates and to perform structural optimization on the molecular model of agglomerates to obtain an optimized molecular model.
[0033] The solution model construction subsystem is used to construct a solution model based on the optimized molecular model;
[0034] The kinetic calculation subsystem is used to perform molecular dynamics calculations based on the fine particulate surface model and the solution model to obtain the agglomerator binding energy, and to complete the screening based on the agglomerator binding energy.
[0035] Compared with the prior art, the beneficial effects of this application are as follows:
[0036] (1) This application can reduce experimental costs and shorten the research and development cycle of agglomerating agents;
[0037] (2) This application predicts the selectivity of fine particulate matter with different components to agglomerate by changing the composition of the surface model;
[0038] (3) This application can further use the model to analyze the interface interaction from the interface state and explore the properties of the material in a deeper way. Attached Figure Description
[0039] To more clearly illustrate the technical solutions of this application, the drawings used in the embodiments are briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0040] Figure 1 This is a schematic diagram of the method flow of an embodiment of this application;
[0041] Figure 2 This is a schematic diagram of the silica surface model structure according to an embodiment of this application;
[0042] Figure 3 This is a schematic diagram of the compound solution model structure according to an embodiment of this application;
[0043] Figure 4 This is a schematic diagram of the overall configuration structure of an embodiment of this application;
[0044] Figure 5 This is a schematic diagram of the overall configuration structure in the equilibrium state of an embodiment of this application;
[0045] Figure 6 This is a schematic diagram of the adsorption dynamic process parameters in an embodiment of this application;
[0046] Figure 7 This is a schematic diagram of the system structure according to an embodiment of this application. Detailed Implementation
[0047] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0048] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.
[0049] Example 1
[0050] In this embodiment, as Figure 1 As shown, a molecular dynamics-based method for screening compound agglomerants includes the following steps:
[0051] S1. Construct a surface model of fine particles.
[0052] The method for constructing a surface model of fine particulate matter includes: performing a cell cutting operation on the fine particulate matter to obtain a two-dimensional structure of the fine particulate matter; adding a vacuum layer of a predetermined thickness on the basis of the two-dimensional structure of the fine particulate matter to obtain a three-dimensional cell of the fine particulate matter; fixing the lower layer atoms of the three-dimensional cell of the fine particulate matter to obtain a surface model of the fine particulate matter.
[0053] When cutting a unit cell, it is necessary to determine the pre-set crystal planes to be cut, the dimensions after supercell cutting, and the thickness of the vacuum layer. During cell expansion, the dimensions should meet the following requirements: length and width greater than twice the van der Waals force radius, and thickness greater than one van der Waals force radius. If covalent bonds are severed during surface cutting, the severed bonds need to be filled in.
[0054] In this embodiment, taking silicon dioxide as an example, the optimized unit cell model is cross-sectioned with a thickness of 10 layers and a supercell of 6*6. The severed Si-O bonds are filled with hydroxyl groups. Because the surface is a two-dimensional structure, a vacuum layer is added to transform it into a three-dimensional unit cell. To prevent interference between the upper and lower surfaces, the thickness of the vacuum layer is set to 15 angstroms. To make the model more closely resemble the characteristics of a real-world surface model, the atoms in the lower layer are fixed, resulting in the silicon dioxide surface model as shown below. Figure 2 As shown.
[0055] S2. Construct a molecular model of the agglomerator and optimize its structure to obtain the optimized molecular model.
[0056] The method for constructing agglomerator molecular models includes: setting the degree of polymerization, number of molecular chains and polymer type, constructing PAM molecular models, SDBS ion models and water molecule models, and combining PAM molecular models and SDBS ion models to obtain agglomerator molecular models.
[0057] In this embodiment, a molecular unit of PAM is constructed, labeled with head and tail hydrogen atoms. The degree of polymerization is set to 10, the chain number to 1, and the polymerization type to be homopolymer, resulting in the PAM molecular model. SDBS exists in solution in ionic form; therefore, a hydrolyzed ionic model and an SDBS ionic model are constructed. Finally, a water molecule model is constructed.
[0058] The structural optimization method includes optimizing the agglomerator molecular model based on the FORCITE module to obtain the configuration with the lowest energy, i.e., the optimized molecular model.
[0059] In this embodiment, the FORCITE module is used for structural optimization of all models required for calculation. A force field type suitable for all atoms needs to be found, while simultaneously checking the correctness of the charges. Structural optimization is performed on all molecules to obtain the configuration with the lowest energy. Because classical force fields are applicable to the SiO2 surface, the classical force field COMPASSⅢ is directly used for model optimization, resulting in the optimized molecular model.
[0060] S3. Based on the optimized molecular model, construct a solution model.
[0061] The solution models include: a complex solution model and a PAM solution model. The complex solution model is constructed based on 5 PAM molecule models, 5 SDBS ion models, and 500 water molecule models. The PAM solution model is constructed based on 5 PAM molecule models and 500 water molecule models.
[0062] In this embodiment, an empty unit cell is created using the Amorphous Cell Calculation module. The previously established molecular model is imported into the Molecule option, containing 5 PAM molecules, 5 SDBS ions, and 500 water molecules. The dimensions of the previously prepared 6*6SiO2 surface model are checked to be 29.478 × 32.4312 Å. The contact surface between the solution and the surface model is adjusted to be equal in length and width. Since the previously set surface model meets the requirements, it is only necessary to ensure that the thickness of the solution model is greater than one van der Waals force cutoff radius. This prepares for the next step of integration. The force field setting in the module is changed to match the force field used in the molecular model, i.e., COMPASSⅢ. Since the imported model has already calculated the charge, the Charges option is set to Usecurrent. The precision is set to "Fine" for structural optimization, resulting in the lowest energy composite solution model, as shown below. Figure 3 Similarly, when importing the molecular model, SDBS ions are not imported; only 5 PAM molecules and 500 water molecules are imported. Subsequent settings are the same as above, resulting in a PAM solution model.
[0063] S4. Molecular dynamics calculations were performed based on the fine particulate surface model and solution model to obtain the agglomerator binding energy, and screening was completed based on the agglomerator binding energy.
[0064] The method for calculating the agglomerator binding energy includes: combining the fine particulate surface model and the solution model to obtain the overall configuration, and calculating the overall single-point energy of the overall configuration; setting the fine particulate surface model as Set A and the solution model as Set B; deleting Set A based on the overall configuration to obtain the first configuration, and calculating the first single-point energy of the first configuration; deleting Set B based on the overall configuration to obtain the second configuration, and calculating the second single-point energy of the second configuration; calculating the agglomerator binding energy based on the overall single-point energy, the first single-point energy, and the second single-point energy, using the following formula:
[0065] ΔE=E total -E surface -E molecule
[0066] Where ΔE represents the agglomerant binding energy, E total E represents the total single-point energy. surface E represents the second single-point energy. molecule This indicates the first single-point energy.
[0067] In this embodiment, a build layer is used to combine the solution model with the silica surface model, and a 20 angstrom thick vacuum layer is added to prevent the upper and lower periodic structures from affecting each other, resulting in the overall configuration, such as... Figure 4 As shown, the final model is used for molecular dynamics calculations, with the ensemble set to NPT and environmental parameters; in this example, the temperature is 298K. The equilibrium state is obtained as follows. Figure 5 Set the SiO2 surface model as Set A and the solution model as Set B. Duplicate the overall configuration after structural optimization three times. Delete Set A from one copy and Set B from the other. Calculate the binding energy for each of the three configurations using the following formula:
[0068] ΔE=E total -E surface -E molecule
[0069] Where ΔE represents the agglomerant binding energy, E total E represents the total single-point energy. surface E represents the single-point energy of the surface model. molecule This represents the single-point energy of the agglomerant molecule model.
[0070] The interfacial adsorption energy between the compound agglomerator and the SiO2 surface was found to be greater than that between the PAM agglomerator and the SiO2 surface. This was calculated using the properties of the FORCITE module and the results were displayed via Analysis. The dynamic process parameters of the agglomerator's adsorption can be obtained from various parameters, such as... Figure 6 Mean square displacement, etc.
[0071] Example 2
[0072] In this second embodiment, as Figure 7 As shown, a molecular dynamics-based complex agglomerator screening system includes: a surface model construction subsystem, a model optimization subsystem, a solution model construction subsystem, and a kinetic calculation subsystem.
[0073] The surface model building subsystem is used to build surface models of fine-grained materials.
[0074] The method for constructing a surface model of fine particulate matter includes: performing a cell cutting operation on the fine particulate matter to obtain a two-dimensional structure of the fine particulate matter; adding a vacuum layer of a predetermined thickness on the basis of the two-dimensional structure of the fine particulate matter to obtain a three-dimensional cell of the fine particulate matter; fixing the lower layer atoms of the three-dimensional cell of the fine particulate matter to obtain a surface model of the fine particulate matter.
[0075] When cutting a unit cell, it is necessary to determine the pre-set crystal planes to be cut, the dimensions after supercell cutting, and the thickness of the vacuum layer. During cell expansion, the dimensions should meet the following requirements: length and width greater than twice the van der Waals force radius, and thickness greater than one van der Waals force radius. If covalent bonds are severed during surface cutting, the severed bonds need to be filled in.
[0076] In this embodiment, taking silicon dioxide as an example, the optimized unit cell model is cross-sectioned with a thickness of 10 layers and a supercell of 6*6. The severed Si-O bonds are filled with hydroxyl groups. Because the surface is a two-dimensional structure, a vacuum layer needs to be added to transform it into a three-dimensional unit cell. To prevent the upper and lower surfaces from interfering with each other, the thickness of the vacuum layer is set to 15 angstroms. To make the model closer to the characteristics of a real surface model, the atoms in the lower layer are fixed to obtain the silicon dioxide surface model.
[0077] The model optimization subsystem is used to construct a molecular model of agglomerates and to optimize the structure of the molecular model of agglomerates to obtain the optimized molecular model.
[0078] The method for constructing agglomerator molecular models includes: setting the degree of polymerization, number of molecular chains and polymer type, constructing PAM molecular models, SDBS ion models and water molecule models, and combining PAM molecular models and SDBS ion models to obtain agglomerator molecular models.
[0079] In this embodiment, a molecular unit of PAM is constructed, labeled with head and tail hydrogen atoms. The degree of polymerization is set to 10, the chain number to 1, and the polymerization type to be homopolymer, resulting in the PAM molecular model. SDBS exists in solution in ionic form; therefore, a hydrolyzed ionic model and an SDBS ionic model are constructed. Finally, a water molecule model is constructed.
[0080] The structural optimization method includes optimizing the agglomerator molecular model based on the FORCITE module to obtain the configuration with the lowest energy, i.e., the optimized molecular model.
[0081] In this embodiment, the FORCITE module is used for structural optimization of all models required for calculation. A force field type suitable for all atoms needs to be found, while simultaneously checking the correctness of the charges. Structural optimization is performed on all molecules to obtain the configuration with the lowest energy. Because classical force fields are applicable to the SiO2 surface, the classical force field COMPASSⅢ is directly used for model optimization, resulting in the optimized molecular model.
[0082] The solution model building subsystem is used to build solution models based on the optimized molecular model.
[0083] The solution models include: a complex solution model and a PAM solution model. The complex solution model is constructed based on 5 PAM molecule models, 5 SDBS ion models, and 500 water molecule models. The PAM solution model is constructed based on 5 PAM molecule models and 500 water molecule models.
[0084] In this embodiment, an empty unit cell is created using the Amorphous Cell Calculation module. The previously established molecular model is imported into the Molecule option, containing 5 PAM molecules, 5 SDBS ions, and 500 water molecules. The dimensions of the previously prepared 6*6SiO2 surface model are checked to be 29.478 × 32.4312 Å. The contact surface between the solution and the surface model is adjusted to be equal in length and width. Since the surface model already meets the requirements, it is only necessary to ensure that the thickness of the solution model is greater than one van der Waals force cutoff radius. This prepares for the next step of integration. The force field setting in the module is changed to match the force field used in the molecular model, i.e., COMPASSⅢ. Since the imported model has already calculated the charge, the Charges option is set to Usecurrent. The precision is set to "Fine" for structural optimization, resulting in the lowest-energy composite solution model. Similarly, SDBS ions are not imported when importing the molecular model; only 5 PAM molecules and 500 water molecules are imported. Subsequent settings are the same as above, resulting in the PAM solution model.
[0085] The kinetic calculation subsystem is used to perform molecular dynamics calculations based on fine particulate surface models and solution models to obtain the agglomerator binding energy, and to complete the screening based on the agglomerator binding energy.
[0086] The method for calculating the agglomerator binding energy includes: combining the fine particulate surface model and the solution model to obtain the overall configuration, and calculating the overall single-point energy of the overall configuration; setting the fine particulate surface model as Set A and the solution model as Set B; deleting Set A based on the overall configuration to obtain the first configuration, and calculating the first single-point energy of the first configuration; deleting Set B based on the overall configuration to obtain the second configuration, and calculating the second single-point energy of the second configuration; calculating the agglomerator binding energy based on the overall single-point energy, the first single-point energy, and the second single-point energy, using the following formula:
[0087] ΔE=E total -E surface -E molecule
[0088] Where ΔE represents the agglomerant binding energy, E total E represents the total single-point energy. surface E represents the second single-point energy. molecule This indicates the first single-point energy.
[0089] In this embodiment, a build layer is used to combine the solution model and the silica surface model. A 20 angstrom thick vacuum layer is added to prevent the upper and lower periodic structures from interfering with each other, resulting in the overall configuration. Molecular dynamics calculations are then performed on the final model, setting the ensemble to NPT and environmental parameters; in this example, the temperature is 298 K. An equilibrium state is obtained. The SiO2 surface model is set as Set A, and the solution model as Set B. Three copies of the overall configuration after structural optimization are made. Set A is deleted from one copy, and Set B is deleted from another. The binding energy is calculated for each of the three configurations using the following formula:
[0090] ΔE×E total -E surface -E molecule
[0091] Where ΔE represents the agglomerant binding energy, E total E represents the total single-point energy. surface E represents the single-point energy of the surface model. molecule This represents the single-point energy of the agglomerant molecule model.
[0092] The interfacial adsorption energy between the compound agglomerator and the SiO2 surface was found to be greater than that between the PAM agglomerator and the SiO2 surface. The properties of the FORCITE module were used to calculate the adsorption energy, and the results were displayed through Analysis. The dynamic process parameters of the agglomerator adsorption, such as the mean square displacement, can be obtained through various parameters.
[0093] The embodiments described above are merely preferred embodiments of this application and are not intended to limit the scope of this application. Any modifications and improvements made to the technical solutions of this application by those skilled in the art without departing from the spirit of this application shall fall within the protection scope defined by the claims of this application.
Claims
1. A method for screening compound agglomerants based on molecular dynamics, characterized in that, Includes the following steps: Construct a surface model of fine particles; A molecular model of an agglomerator was constructed, and the structure of the agglomerator molecular model was optimized to obtain an optimized molecular model. Based on the optimized molecular model, a solution model is constructed; Molecular dynamics calculations were performed based on the fine particulate matter surface model and the solution model to obtain the agglomerator binding energy, and screening was completed based on the agglomerator binding energy. The method for constructing the agglomerator molecular model includes: setting the degree of polymerization, number of molecular chains and polymer type, constructing a PAM molecular model, an SDBS ion model and a water molecule model, and combining the PAM molecular model and the SDBS ion model to obtain the agglomerator molecular model; The structure optimization method includes: optimizing the agglomerant molecular model based on the FORCITE module to obtain the configuration with the lowest energy, i.e., the optimized molecular model; The solution models include: a compound solution model and a PAM solution model; The method for constructing the complex solution model includes: constructing the complex solution model based on 5 PAM molecule models, 5 SDBS ion models and 500 water molecule models; The method for constructing the PAM solution model includes: constructing the PAM solution model based on 5 PAM molecule models and 500 water molecule models; The method for calculating the binding energy of the agglomerating agent includes: The fine particulate matter surface model and the solution model are combined to obtain the overall configuration, and the overall single-point energy of the overall configuration is calculated. The surface model of the fine particulate matter is set as Set A, and the solution model is set as Set B; Based on the overall configuration, Set A is deleted to obtain the first configuration, and the first single-point energy of the first configuration is calculated; Based on the overall configuration, Set B is deleted to obtain a second configuration, and the second single-point energy of the second configuration is calculated; The agglomerant binding energy is calculated based on the overall single-point energy, the first single-point energy, and the second single-point energy. The formula for calculating the binding energy of the agglomerant is as follows: ΔE=E total -E surface -E molecule Where ΔE represents the agglomerant binding energy, E total E represents the total single-point energy. surface E represents the second single-point energy. molecule This indicates the first single-point energy.
2. The method for screening compound agglomerants based on molecular dynamics according to claim 1, characterized in that, The method for constructing the fine particulate matter surface model includes: By performing a unit cell cutting operation on the fine particulate matter, a two-dimensional structure of the fine particulate matter is obtained; A vacuum layer of predetermined thickness is added to the two-dimensional structure of the fine particulate matter to obtain a three-dimensional unit cell of the fine particulate matter. By fixing the lower-layer atoms of the three-dimensional unit cell of the fine particles, a surface model of the fine particles is obtained.
3. A molecular dynamics-based system for screening compound agglomerates, wherein the system employs the method described in any one of claims 1-2, characterized in that, It includes: a surface model construction subsystem, a model optimization subsystem, a solution model construction subsystem, and a kinetic calculation subsystem; The surface model construction subsystem is used to construct a surface model of fine particles; The model optimization subsystem is used to construct a molecular model of agglomerates and to perform structural optimization on the molecular model of agglomerates to obtain an optimized molecular model. The solution model construction subsystem is used to construct a solution model based on the optimized molecular model; The kinetic calculation subsystem is used to perform molecular dynamics calculations based on the fine particulate surface model and the solution model to obtain the agglomerator binding energy, and to complete the screening based on the agglomerator binding energy.