A method for modeling the solid-liquid interface at the atomic level in the hydration process of solid waste-based polymers dominated by a Si-Al-Si skeleton
By using a molecular dynamics simulation method dominated by the Si-Al-Si framework, a molecular structure model of Si9Al4O36 was constructed, which solved the problems of lack of modeling specifications and incomplete characterization of the initial hydration process in existing technologies, and achieved accurate characterization and theoretical support for the polymer hydration process in solid waste bases.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HEBEI SHITAI EXPRESSWAY DEV CO LTD
- Filing Date
- 2026-01-21
- Publication Date
- 2026-06-12
AI Technical Summary
Existing molecular dynamics simulation methods lack unified modeling standards in the study of polymer hydration processes in solid waste sites. The differences in force field selection and parameter settings make it difficult to guarantee the reliability and comparability of simulation results. Furthermore, they neglect the key processes in the early stages of hydration, making it difficult to truly reflect the actual hydration reaction scenario.
A Si-Al-Si framework-dominated approach was used to construct a molecular structure model of Si9Al4O36. Molecular dynamics simulations were then used to simulate the hydration process at the atomic scale, including the construction of an initial amorphous unit cell model and an H2O model, followed by geometric optimization and NVT equilibration processing. Data such as radial distribution function, interfacial adsorption energy, axial concentration, and number of hydrogen bonds were obtained.
The core framework features of the solid waste substrate polymer gel were realistically reproduced at the atomic scale, revealing the interfacial interaction mechanism and ion diffusion behavior in the early stage of the hydration reaction, and providing a complete description of the hydration mechanism.
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Figure CN122201465A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of molecular dynamics technology, and more specifically, to an atomic-level modeling method for the solid-liquid interface in the hydration process of solid waste-based polymers dominated by a Si-Al-Si framework. Background Technology
[0002] Solid waste aggregates, as a novel type of cementitious material, primarily produce calcium aluminosilicate hydrate as their hydration product. Therefore, the atomic coordination structure, interfacial bonding state, and hydrogen bond network of calcium aluminosilicate hydrate directly influence the material's macroscopic mechanical properties and long-term service stability. However, traditional research mainly relies on macroscopic experimental methods, making it difficult to accurately capture the interaction mechanisms during the hydration process at the atomic scale. This limits the analysis of the formation mechanism of calcium aluminosilicate hydrate.
[0003] In recent years, molecular dynamics (MD) simulations have provided a new approach for atomic-scale modeling of polymers in solid waste sites. Through molecular dynamics simulations, researchers can build models at the atomic scale to simulate molecular behavior and interfacial reactions during hydration. This method can compensate for the limitations of macroscopic experiments and provide a more in-depth theoretical basis for revealing the hydration mechanism.
[0004] However, existing molecular dynamics simulation methods still have significant shortcomings when applied to the study of polymer hydration processes in solid waste sites: First, there is a lack of unified modeling standards for the calcium aluminosilicate hydrate (CASH) system, leading to significant differences in force field selection and parameter settings among researchers, making it difficult to guarantee the reliability and comparability of simulation results; Second, the design of reactant systems lacks clear standards when constructing solid-liquid interface models, often resulting in insufficient force field adaptability or missing characterization of key chemical environmental features, making it difficult to realistically reflect the actual hydration reaction scenario; Third, current research focuses more on the formation and evolution of late-stage hydration products, neglecting key processes such as interfacial adsorption, ion diffusion, and hydrolysis initiation during the initial contact between solid waste precursors and water, resulting in an incomplete characterization of the hydration mechanism. Therefore, there is an urgent need to construct a systematic and accurate atomic-level modeling method for the solid-liquid interface in the solid waste site polymer hydration process to fill the existing technological gaps and provide reliable theoretical support for achieving cross-scale correlation between nanoscale-microscale structure and macroscopic properties.
[0005] No effective solutions have yet been proposed to address the problems in the relevant technologies. Summary of the Invention
[0006] To address the shortcomings of existing technologies, this invention provides an atomic-level modeling method for the solid-liquid interface in the hydration process of polymers in solid waste sites, dominated by a Si-Al-Si framework. This method has the advantages of systematically constructing a solid-liquid interface model and accurately characterizing the atomic-level interaction mechanism in the early stage of the hydration reaction. It also solves the problems of lack of modeling specifications, unclear solid-liquid interface design standards, and incomplete characterization of key processes in the early stage of hydration in existing molecular dynamics simulation methods for studying the hydration process of polymers in solid waste sites.
[0007] To achieve the advantages of the above-mentioned system in constructing a solid-liquid interface model and accurately characterizing the atomic-level interaction mechanism in the early stage of hydration reaction, the specific technical solution adopted in this invention is as follows: An atomic-level modeling method for the solid-liquid interface of solid waste-based polymer hydration processes dominated by a Si-Al-Si framework is proposed, comprising: testing the main chemical elements, crystal structure, and phase composition of the solid waste-based polymer; screening out the main elements and constructing a molecular structure model; and assigning force fields and charges to the main elements and the molecular structure model; wherein the main elements include Na. + Ca 2+ and Mg 2+ The molecular structure model includes Si9Al4O 36 Molecular structure: Molecular structure models are randomly dispersed in cubic unit cells to construct initial amorphous unit cell models and H2O models; the initial amorphous unit cell model and H2O model are combined to obtain a solid-liquid interface model, and the solid-liquid interface model is geometrically optimized; the geometrically optimized solid-liquid interface model is subjected to NVT equilibrium treatment to obtain a stable solid-liquid interface model; molecular dynamics simulations are performed on the stable solid-liquid interface model to obtain relevant data; the relevant data include radial distribution function, interfacial adsorption energy, axial concentration, mean square displacement, and number of hydrogen bonds.
[0008] Furthermore, the composition of the main chemical elements of the solid waste-based polymer was tested, which was used to determine the chemical elements and element ratios required for modeling based on the main chemical composition ratio of the solid waste-based polymer; the crystal structure and phase composition of the solid waste-based polymer were tested, which was used to verify the reliability of the modeling by comparing the matching degree between the constructed amorphous unit cell model and the measured XRD diffraction peaks.
[0009] Furthermore, Si9Al4O 36 The molecular structure is determined by the main hydration products of the geopolymer gel; the main hydration product is [SiO4]. 4- Tetrahedron and [AlO4] 5- Tetrahedrons are three-dimensional network amorphous or semi-crystalline materials formed by polymerization reactions; in this main hydration product, Si is the central atom, and Al and O atoms are connected around the central atom, and the Al atoms are connected to the Si atoms to form a network structure.
[0010] Furthermore, constructing the molecular structure model involves adding Si atoms and building four O atoms coordinated and connected to the Si atoms at the center, forming [SiO4]. 4- Tetrahedral; Al atoms are respectively combined with [SiO4] 4- The four vertices of the tetrahedron are connected by O atoms, and three additional O atoms are connected to each Al atom to form [AlO4]. 5- The tetrahedral coordination environment is formed by using three O atoms surrounding each Al atom as connection sites, with one Si atom attached to each of these sites, and then constructing four fully coordinated O atoms for each of these attached Si atoms to form Si9Al4O. 36 The skeletal structure was obtained, and the molecular structure model was derived.
[0011] Furthermore, assigning force fields and charges to the main element and molecular structure model includes: selecting a preset force field type and a preset charge allocation method; based on the preset force field type and preset charge allocation method, assigning force fields and charges to Na respectively. + Ca 2+ and Mg 2+ and Si9Al4O 36 The molecular structure model completes the force field and charge allocation; disable the automatic calculation option and the force field type list option to complete the force field and charge allocation operation.
[0012] Furthermore, constructing the initial amorphous unit cell model and the H2O model includes: inputting Na based on the composition ratio of the main elements. + Ca 2+ and Mg 2+ The number of Si9Al4O 36 The molecular chain polymerization degree of the molecular structure is set, and preset mass parameters, preset density parameters, and preset output frame number are set to complete the distribution of the molecular structure model and the construction of the initial amorphous unit cell model; select H2O molecules, input the number of H2O molecules to be added, and set preset mass parameters, preset density parameters, and preset output frame number to complete the construction of the H2O model.
[0013] Furthermore, the initial amorphous cell model is combined with the H2O model to obtain a solid-liquid interface model, which includes ensuring that the length, width, height, and angle of the H2O model are completely consistent with the settings of the initial amorphous cell model; wherein, the length and width of both the initial amorphous cell model and the H2O model are greater than a first multiple of the preset cutoff radius, and the height of both the initial amorphous cell model and the H2O model is greater than a second multiple of the preset cutoff radius; the initial amorphous cell model is used as the first layer, the H2O model is used as the second layer, a vacuum layer of preset thickness is added above the H2O model, and the first layer is selected as the matching reference to form a solid-liquid interface model.
[0014] Furthermore, the geometric optimization of the solid-liquid interface model includes: adopting a preset optimization algorithm and setting the calculation accuracy, maximum number of iterations and force field type; based on the preset optimization algorithm, combined with electrostatic force calculation and van der Waals force calculation, correcting the bond configuration and atomic charge distribution in the solid-liquid interface model to obtain a molecular structure model with lower energy.
[0015] Furthermore, the NVT equilibration process for the geometrically optimized solid-liquid interface model includes: controlling the simulation process through the NVT ensemble and setting the initial velocity type, temperature, time step, and total simulation duration; dividing the total simulation duration into a system preheating equilibration stage and a data acquisition stage according to a preset ratio, and recording the system trajectory at preset time intervals; selecting the thermostat type and force field type, and combining electrostatic force calculation and van der Waals force calculation to obtain a stable solid-liquid interface model.
[0016] Furthermore, molecular dynamics simulations were performed on the stable solid-liquid interface model, yielding the following data: Based on the stable solid-liquid interface model, a cutoff radius and spacing distance were set, and the characteristic peak positions of the target bonds in the stable solid-liquid interface model were obtained through radial distribution function analysis to verify the rationality of the coordination structure of the stable solid-liquid interface model; the target bonds include Si-O bonds, Al-O bonds, and H2O bonds; the interfacial adsorption energy of the solid-liquid interface of the stable solid-liquid interface model was calculated to verify that the stable solid-liquid interface model conforms to the spontaneous adsorption between solid waste particles and water molecules; the axial concentration of the solid-liquid interface of the stable solid-liquid interface model was calculated to directly characterize the degree of directional aggregation of hydration products and the direction of the activation reaction interface of solid waste particles; the diffusion coefficient of ions was obtained through mean square displacement calculation to characterize the ion migration propagation rate during the hydration reaction of the solid waste geopolymer; and the number of hydrogen bonds at the solid-liquid interface of the stable solid-liquid interface model was counted through hydrogen bond analysis to quantify the degree of hydration of the solid waste geopolymer during the hydration process.
[0017] Compared with existing technologies, this invention provides an atomic-level modeling method for the solid-liquid interface in the hydration process of polymers in solid waste sites dominated by a Si-Al-Si framework, which has the following beneficial effects: (1) This invention constructs Si9Al4O 36 The molecular structure model accurately reproduces the core framework characteristics of the solid waste geopolymer gel at the atomic scale. This molecular structure model is designed based on the chemical nature of the main hydration products of the geopolymer, namely [SiO4]. 4- Tetrahedron and [AlO4] 5- The three-dimensional network structure formed by the coordination of tetrahedrons can accurately characterize the coordination environment and chemical bond characteristics of the Si-Al-Si framework during hydration, providing a reliable structural basis for subsequent force field distribution, interface simulation and performance analysis.
[0018] (2) In constructing the solid-liquid interface model, the present invention combines the initial amorphous cell model with the H2O model to simulate the interfacial adsorption process in the initial stage of contact between solid waste particles and water molecules. This modeling approach makes up for the shortcomings of the existing technology, which only focuses on the evolution process after the formation of hydration products. At the same time, through geometric optimization of the solid-liquid interface, NVT equilibrium treatment and molecular dynamics simulation, the interfacial interaction mechanism, ion diffusion behavior and hydrogen bond network evolution law of the initiation stage of solid waste base polymer hydration reaction can be systematically revealed, thus providing an atomic-level theoretical basis for a complete description of the hydration mechanism. Attached Figure Description
[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0020] Figure 1 This is a flowchart illustrating an atomic-level modeling method for the solid-liquid interface of a solid waste-based polymer hydration process dominated by a Si-Al-Si framework, according to an embodiment of the present invention. Figure 2 This is a schematic diagram of molecular ions used in an atomic-level modeling method for the solid-liquid interface of a solid waste base polymer hydration process dominated by a Si-Al-Si framework, according to an embodiment of the present invention. Figure 3 This is a schematic diagram of the construction of a solid-liquid interface model in an atomic-level modeling method for the solid-liquid interface of a solid waste base polymer hydration process dominated by a Si-Al-Si framework, according to an embodiment of the present invention. Figure 4 This is a temperature change diagram during the geometric optimization of the solid-liquid interface model in an atomic-level modeling method for the solid-liquid interface of a solid waste base polymer hydration process dominated by a Si-Al-Si framework, according to an embodiment of the present invention. Figure 5 This is a diagram showing the result of calculating axial concentration in an atomic-level modeling method for the solid-liquid interface of a solid waste base polymer hydration process dominated by a Si-Al-Si framework, according to an embodiment of the present invention. Figure 6 This is a graph showing the results of radial distribution function analysis in an atomic-level modeling method for the solid-liquid interface of a solid waste base polymer hydration process dominated by a Si-Al-Si framework, according to an embodiment of the present invention. Figure 7 This is a graph showing the number of hydrogen bonds at the solid-liquid interface in a statistically stable solid-liquid interface model, based on an atomic-level modeling method for the solid-liquid interface of a Si-Al-Si framework-dominated solid waste polymer hydration process according to an embodiment of the present invention. Detailed Implementation
[0021] To further illustrate the various embodiments, the present invention provides accompanying drawings, which are part of the disclosure of the present invention. These drawings are mainly used to illustrate the embodiments and can be used in conjunction with the relevant descriptions in the specification to explain the operating principles of the embodiments. With reference to these drawings, those skilled in the art should be able to understand other possible implementation methods and the advantages of the present invention. The components in the drawings are not drawn to scale, and similar component symbols are generally used to represent similar components.
[0022] According to embodiments of the present invention, an atomic-level modeling method for the solid-liquid interface in the hydration process of polymers in solid waste sites dominated by a Si-Al-Si framework is provided.
[0023] The present invention will now be further described in conjunction with the accompanying drawings and specific embodiments, such as... Figure 1 As shown, an atomic-level modeling method for the solid-liquid interface of a Si-Al-Si framework-dominated solid waste-based polymer hydration process, according to an embodiment of the present invention, includes: testing the main chemical elements, crystal structure, and phase composition of the solid waste-based polymer; based on the main chemical elements, crystal structure, and phase composition of the solid waste-based polymer, screening out the main elements, constructing a molecular structure model, and assigning force fields and charges to the main elements and the molecular structure model; wherein, the main elements include Na. + Ca 2+ and Mg 2+ The molecular structure model includes Si9Al4O 36 Molecular structure: Molecular structure models are randomly dispersed in cubic unit cells to construct initial amorphous unit cell models and H2O models; the initial amorphous unit cell model and H2O model are combined to obtain a solid-liquid interface model, and the solid-liquid interface model is geometrically optimized; the geometrically optimized solid-liquid interface model is subjected to NVT equilibrium treatment to obtain a stable solid-liquid interface model; molecular dynamics simulations are performed on the stable solid-liquid interface model to obtain relevant data; the relevant data include radial distribution function, interfacial adsorption energy, axial concentration, mean square displacement, and number of hydrogen bonds.
[0024] In one embodiment, the composition of the main chemical elements of the solid waste-based polymer is tested to determine the chemical elements and element ratios required for modeling based on the proportion of the main chemical composition of the solid waste-based polymer; the crystal structure and phase composition of the solid waste-based polymer are tested to verify the reliability of the modeling by comparing the matching degree between the constructed amorphous unit cell model and the measured XRD diffraction peaks.
[0025] In one embodiment, Si9Al4O 36 The molecular structure is determined by the main hydration products of the geopolymer gel; the main hydration product is [SiO4]. 4-Tetrahedron and [AlO4] 5- Tetrahedrons are three-dimensional network amorphous or semi-crystalline materials formed by polymerization reactions; in this main hydration product, Si is the central atom, and Al and O atoms are connected around the central atom, and the Al atoms are connected to the Si atoms to form a network structure.
[0026] In one embodiment, such as Figure 2 As shown, constructing the molecular structure model involves adding Si atoms and building four O atoms coordinated and connected to the Si atoms, forming [SiO4]. 4- Tetrahedral; Al atoms are respectively combined with [SiO4]. 4- The four vertices of the tetrahedron are connected by O atoms, and three additional O atoms are connected to each Al atom to form [AlO4]. 5- The tetrahedral coordination environment is formed by using three O atoms surrounding each Al atom as connection sites, with one Si atom attached to each of these sites, and then constructing four fully coordinated O atoms for each of these attached Si atoms to form Si9Al4O. 36 The skeletal structure was obtained, and the molecular structure model was derived.
[0027] In one embodiment, assigning force fields and charges to the main element and molecular structure model includes: selecting a preset force field type and a preset charge assignment method; and, based on the preset force field type and preset charge assignment method, assigning force fields and charges to Na respectively. + Ca 2+ and Mg 2+ and Si9Al4O 36 The molecular structure model completes the force field and charge allocation; disable the automatic calculation option and the force field type list option to complete the force field and charge allocation operation.
[0028] In one embodiment, constructing the initial amorphous unit cell model and the H2O model includes: inputting Na based on the composition ratio of the major elements. + Ca 2+ and Mg 2+ The number of Si9Al4O 36 The molecular chain polymerization degree of the molecular structure is set, and preset mass parameters, preset density parameters, and preset output frame number are set to complete the distribution of the molecular structure model and the construction of the initial amorphous unit cell model; select H2O molecules, input the number of H2O molecules to be added, and set preset mass parameters, preset density parameters, and preset output frame number to complete the construction of the H2O model.
[0029] In one embodiment, such as Figure 3As shown, the initial amorphous unit cell model is combined with the H2O model to obtain a solid-liquid interface model, including ensuring that the length, width, height, and angle of the H2O model are completely consistent with the initial amorphous unit cell model; wherein, the length and width of both the initial amorphous unit cell model and the H2O model are greater than a first multiple of the preset cutoff radius, and the height of both the initial amorphous unit cell model and the H2O model is greater than a second multiple of the preset cutoff radius; the initial amorphous unit cell model is used as the first layer, the H2O model is used as the second layer, a vacuum layer of preset thickness is added above the H2O model, and the first layer is selected as the matching reference to form the solid-liquid interface model.
[0030] In one embodiment, such as Figure 4 As shown, the geometric optimization of the solid-liquid interface model includes: using a preset optimization algorithm and setting the calculation accuracy, maximum number of iterations and force field type; based on the preset optimization algorithm, combined with electrostatic force calculation and van der Waals force calculation, correcting the bond configuration and atomic charge distribution in the solid-liquid interface model to obtain a molecular structure model with lower energy.
[0031] In one embodiment, performing NVT equilibration processing on the geometrically optimized solid-liquid interface model includes: controlling the simulation process through the NVT ensemble and setting the initial velocity type, temperature, time step, and total simulation duration; dividing the total simulation duration into a system preheating equilibration stage and a data acquisition stage according to a preset ratio, and recording the system trajectory at preset time intervals; selecting the thermostat type and force field type, and combining electrostatic force calculation and van der Waals force calculation to obtain a stable solid-liquid interface model.
[0032] In one embodiment, molecular dynamics simulations are performed on the stable solid-liquid interface model to obtain relevant data, including: based on the stable solid-liquid interface model, setting the cutoff radius and spacing distance, and obtaining the characteristic peak positions of the target bonds in the stable solid-liquid interface model through radial distribution function analysis, such as... Figure 6 As shown, the rationality of the coordination structure of the stable solid-liquid interface model is verified; the target bonds include Si-O bonds, Al-O bonds, and H2O bonds; the interfacial adsorption energy of the solid-liquid interface of the stable solid-liquid interface model is calculated to verify that the stable solid-liquid interface model conforms to the spontaneous adsorption between solid waste particles and water molecules; as shown. Figure 5 As shown, axial concentration calculations were performed on the solid-liquid interface of the stable solid-liquid interface model to directly characterize the degree of directional aggregation of hydration products and the propagation direction of the activation reaction interface of solid waste particles; the diffusion coefficient of ions was obtained through mean square displacement calculation to characterize the propagation rate of ion migration during the hydration reaction of solid waste aggregates; and the number of hydrogen bonds at the solid-liquid interface of the stable solid-liquid interface model was counted through hydrogen bond analysis. Figure 7 As shown, the degree of hydration of solid waste polymers during the hydration process is quantified.
[0033] It should be noted that this invention discloses a solid-liquid interface modeling method for the solid-liquid interface process of polymer hydration in solid waste sites dominated by a Si-Al-Si framework. This method aims to solve the technical problems of inaccurate reactant structure, poor force field adaptability, and unsystematic parameter control in existing solid-liquid interface modeling methods for polymer hydration in solid waste sites. The method first constructs H2O and Ca... 2+ Na + Mg 2+ and Si9Al4O 36 (Si-Al-Si); then, an amorphous unit cell and H2O structure model are constructed; finally, the two models are combined into a solid-liquid interface model. This method includes the following steps: I. Test the main chemical element composition, crystal structure, and phase composition of the polymers in the solid waste base; II. Screening for the main element Na + Ca 2+ Mg 2+ And construct Si9Al4O 36 Molecular structure, for Na + Ca 2+ Mg 2+ Si9Al4O 36 Molecular structure models assign force fields and charges; III. Disperse the molecular model randomly in a cubic unit cell to construct an initial amorphous unit cell model and an H2O model; IV. Combine the models to form a solid-liquid interface model and perform geometric optimization; V. Perform NVT balancing on the geometrically optimized solid-liquid interface model to obtain a more stable model; VI. Molecular dynamics simulations were performed on a stable solid-liquid interface model to obtain relevant data such as radial distribution function, interfacial adsorption energy, axial concentration, mean square displacement, and number of hydrogen bonds.
[0034] Specifically, in step I, the main chemical element composition of the solid waste base polymer is tested. The core purpose is to determine the chemical elements and element ratios required for modeling based on the proportions of its main chemical components. Testing the crystal structure and phase composition verifies the reliability of the modeling by comparing the matching degree between the constructed amorphous unit cell model and the measured XRD diffraction peaks. Among these, Si9Al4O 36 The molecular structure is determined by the nature of the main hydration products of the geopolymer gel; these hydration products are essentially [SiO4]. 4- Tetrahedron and [AlO4] 5-Tetrahedrons are three-dimensional network amorphous or semi-crystalline materials formed through polymerization reactions. Si serves as the central atom, surrounded by Al and O atoms, and the Al atoms further connect with new Si atoms to form a network structure. Therefore, a Si to Al atom ratio of 9:4 is selected.
[0035] Specifically, in step II, the main molecular structure of the solid-liquid interface is Si9Al4O. 36 The design process for (Si-Al-Si) involves: using the 3D Atomistic feature of Materials Studio software, first introducing a core atom and constructing a basic coordination structure; then adding Si atoms and building four O atoms coordinated to them to form [SiO4]. 4- Tetrahedral units; then Al atoms are respectively reacted with [SiO4]. 4- The four vertices of the tetrahedron are connected by O atoms, and each Al atom is additionally connected to three O atoms to form [AlO4]. 5- Tetrahedral coordination environment. Then, using the three newly added O atoms around each Al atom as connection sites, one Si atom is attached to each of these attached Si atoms, and four fully coordinated O atoms are built for each of these attached Si atoms, ultimately forming the composition Si9Al4O. 36 The skeletal structure.
[0036] Specifically, in step II, the allocation of force fields and charges to atoms and molecules includes: selecting Modules, clicking Calculation in Forcite, selecting COMPASS II force field in Forcefield, selecting Forcefield as assigned in Charges, and unchecking Calculate automatically and List all forcefield types in Forcite Preparation Options. Then, click Calculate and Assign respectively to complete the allocation of force fields and charges to different atomic and molecular structures.
[0037] Specifically, in step III, the molecular model is randomly dispersed in a cubic unit cell to construct the initial amorphous unit cell model and the H2O model. The specific architecture operation and parameter settings are as follows: 1) Construct the initial amorphous unit cell model, that is, use the Amorphous Cell Calculation module of Materials Studio software, and input Na based on the above-mentioned composition ratio of the main elements. + Ca 2+ Mg 2+ The number of Si9Al4O 36For the molecular structure, the degree of polymerization of the molecular chains is selected as Medium for Quality and 1.7 g / cm³ for Density. 3 1) Select 10 frames for Output and click Run to complete the distribution of the molecular model and the construction of the amorphous unit cell model; 2) Construct the H2O model, i.e., use the Amorphous Cell Calculation module of Materials Studio software, select the H2O molecule, and enter the number of H2O molecules to be added. Select Medium for Quality and 1.0 g / cm³ for Density. 3 Select 10 frames for Output to complete the construction of the H2O model.
[0038] Specifically, the steps to combine the models into a solid-liquid interface model are as follows: In Task, select Confined Layer, ensuring that the length, width, height, and angles of the H2O model are completely consistent with the amorphous unit cell model. The settings must satisfy that the length and width are greater than twice the preset cutoff radius Rcut, and the thickness of each layer is greater than one Rcut. Open the interfaces of the two models to be combined, click Build, and select Build Layer. For Layer 1, select the amorphous unit cell; for Layer 2, select H2O. Add a 30 Å vacuum layer above the H2O layer. In Matching, select Layer 1 as the matching reference, and click Build to construct the solid-liquid interface model.
[0039] Specifically, in step IV, geometric optimization of the solid-liquid interface is performed, including: clicking ForciteCalculation and selecting Geometry Optimization, where the calculation accuracy is set to Medium, the steepest, quasi-Newton, and Newton-Raphson algorithms are used, the maximum number of iterations is set to 10,000, the force field is set to COMPASS, electrostatic forces are calculated using PPM, and van der Waals forces are calculated using atom-based methods. By correcting the bond configuration and atomic charge distribution, the structure of each model is made more reasonable, resulting in a monomer molecule model with extremely low energy.
[0040] Specifically, step V involves performing NVT equilibrium processing on the solid-liquid interface, including: opening ForciteCalculation and selecting the Dynamics module to perform molecular dynamics simulations of the solid-liquid interface. In molecular dynamics simulations, microcanonical ensembles (NVE), canonical ensembles (NVT), and isothermal-isobaric ensembles (NPT) are three fundamental thermodynamic ensembles, and their selection must be closely combined with the characteristics of the simulation system and the core research objectives. This invention involves the construction of a solid-liquid interface model, and temperature is a key factor affecting the microscopic behavior of the solid-liquid interface; therefore, it is required that the system temperature remain constant during the simulation. Based on this, the canonical ensemble NVT is selected for simulation calculations. This ensemble can accurately maintain the particle number N, volume V, and temperature T of the system through temperature control algorithms, providing stable thermodynamic conditions for exploring the microscopic mechanisms related to the solid-liquid interface.
[0041] The simulation was conducted using an NVT ensemble control system. The initial velocity was set to Random, the temperature to 298 K, and the time step to 1 fs, with a total simulation duration of 5000 ps. The first 1000 ps was for system preheating and equilibrium, and the following 4000 ps was for data acquisition. The system trajectory (atomic coordinates, energy, temperature, etc.) was recorded every 10 ps for subsequent analysis. The thermostat was Nose, the force field was COMPASS, and PPM was used to calculate electrostatic forces, while atom-based simulations were used to calculate van der Waals forces.
[0042] Specifically, step VI involves simulating and evaluating the reaction at the solid-liquid interface, including the following steps: ① Select Modules, click Forcite, then select Radial Distribution Function in Analysis to perform the analysis. The Cutoff is 10 Å; the Interval is 0.05 Å. The calculated Radial Distribution Function (RDF) result is both a key verification basis for the model's accuracy and a core analytical indicator of the system's nanoscale structure. The characteristic peak positions of Si-O, Al-O, and HO bonds obtained through RDF analysis all fall within the characteristic bond length range of the calcium aluminosilicate hydrate (CASH) system, confirming the rationality of the model's nanoscale coordination structure.
[0043] ② Add the code "Eint components for XTD" to the MS software to calculate the interfacial adsorption energy at the solid-liquid interface. The interfacial interaction energy (Eint, or binding energy) serves a dual purpose: the formation of geopolymer strength from solid waste is essentially a process of hydrolysis-condensation reaction between the solid waste particles and water, and the prerequisite for this reaction is the spontaneous adsorption between the solid waste particles and water molecules. From a thermodynamic perspective, the interfacial interaction energy corresponding to the spontaneous adsorption process must be negative. This result directly corroborates the model's consistency with the reaction's essence and provides quantitative support for the interfacial interaction mechanism of geopolymer formation.
[0044] ③ Following the same steps as ①, select Mean Square Displacement in Analysis to calculate the mean square displacement (MSD). The diffusion coefficient of ions reflects the microscopic migration ability of ions in the cementing system and indirectly characterizes the rate of advancement of the hydration reaction; the number of hydrogen bonds directly reflects the interaction strength between water molecules and cementing material components and water molecules within the system, and is one of the key microscopic indicators for quantifying the degree of hydration of the system.
[0045] ④ Import the H-bond bet 2 parts code into MS software to perform hydrogen bond analysis on the solid-liquid interface, so as to intuitively reflect the degree of hydration of the solid-liquid interface.
[0046] Specifically, although the operation demonstration of the technical solution of the present invention in the above embodiments uses Materials Studio software as the carrier, similar molecular dynamics simulation operations can be achieved in other molecular dynamics software. Considering that commercial software is usually expensive, a more economical and practical choice is to use open-source software such as GROMACS and LAMMPS. Those skilled in the art only need to follow the aforementioned operational logic and step sequence to complete the corresponding simulation modeling operations by combining the software syntax of GROMACS and LAMMPS.
[0047] To facilitate understanding of the above technical solution of the present invention, the following detailed description is based on a multi-component solid waste mineral binder.
[0048] This embodiment employs Materials Studio software to implement an atomic-level modeling method for the solid-liquid interface of a solid waste-based polymer hydration process dominated by a Si-Al-Si framework. X-ray fluorescence spectrometry was used to test the main chemical elemental composition of the solid waste-based polymer sample, determining that it mainly contains Si, Al, O, Na, Ca, and Mg. X-ray diffraction was used to test its crystal structure and phase composition, obtaining XRD diffraction patterns for subsequent model verification. Based on the test results, the main elements Na, Ca, and Mg were selected, and the required number of ions for modeling was determined according to the molar ratio of each element. This embodiment includes the following steps: Step 1: Select Na, Ca, Mg atoms and Si9Al4O 36 And H2O molecules, and determine the molar ratio of each monomer; then, using the 3D Atomistic modeling method of Materials Studio software, construct Na, Ca, Mg atoms and Si9Al4O3 respectively. 36 And H2O molecules.
[0049] Step 2: In the Forcite Calculation function within the Forcite module of Materials Studio software, analyze the Na, Ca, Mg atoms and Si9Al4O3 atoms. 36 In addition, H2O molecules are charged and subjected to the COMPASS force field, causing Na, Ca, and Mg to transform into Na. + Ca 2+ Mg 2 + .
[0050] Step 3: Using the Amorphous Cell Calculation module of Materials Studio software, determine the Na content according to the molar ratio determined in Step 1. + Ca 2+ Mg 2+ The number of ions and Si9Al4O 36 The degree of polymerization and the density of amorphous cells.
[0051] Step 4: In Lattice Parameters, modify the model's dimensions (length, width, and height) to ensure that the length and width are greater than twice the Rcut, and the height of each layer is greater than once the Rcut. α, β, and γ are each set to 90°.
[0052] Step 5: Similarly, in the Amorphous Cell Calculation module, select the configured H2O molecule, select Confined Layer in Task, and ensure that the model dimensions (length, width, height, and angles) are exactly the same as those of the amorphous cell set above.
[0053] Step 6: Add H2O molecules and perform simulation calculations.
[0054] Step 7: In the trajectory file of the calculation results, observe and compare to find the frame with the lowest energy. In the attribute manager, select Trajectory, click CurrentFrame, and enter the frame with the lowest energy to select it.
[0055] Step 8: Create a new 3D Atomistic interface and copy and paste the selected minimum frame rate into it.
[0056] Step 9, then click File > Save project to save the current calculation results.
[0057] Step 10: Click "Close All" in Window to clear the interface.
[0058] Step 11: Open the interfaces of the two models that need to be combined, click Build and select Build Layer. In Layer 1, select amorphous cell; in Layer 2, select H2O.
[0059] Step 12: Add a 30 Å vacuum layer above the H2O layer, and select Layer 1 as the matching reference in Matching.
[0060] Step 13: Click "Forcite Calculation" and select "Geometry Optimization" to perform geometric optimization on the generated solid-liquid interface model. This optimizes the bond configuration and atomic charge distribution to make the model structure more reasonable, resulting in a monomer molecule model with extremely low energy. The calculation accuracy is set to "Medium," and the steepest, quasi-Newton, and Newton-Raphson algorithms are used. The maximum number of iterations is set to 10,000. The force field is set to "COMPASS," and the electrostatic force is calculated using PPM, while the van der Waals force is calculated using an atom-based algorithm.
[0061] Step 14: Open Forcite Calculation and select the Dynamics module to perform a molecular dynamics simulation of the solid-liquid interface. Select NVT ensemble control for the simulation process, choose Random for the initial velocity, 298K for the temperature, set the time step to 1 fs, and the total simulation duration to 5000 ps. The first 1000 ps is for system preheating and equilibrium, and the last 4000 ps is for data acquisition. Record the system trajectory (atomic coordinates, energy, temperature, etc.) every 10 ps for subsequent analysis. Select Nose as the thermostat and COMPASS as the force field. Use PPM to calculate electrostatic forces and Atom-based methods to calculate van der Waals forces.
[0062] After the above optimization, the density of the obtained stable unit cell model converges, resulting in a stable solid-liquid model with the lowest energy and the least intermolecular stress.
[0063] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.
Claims
1. An atomic-level modeling method for the solid-liquid interface in the hydration process of polymers in solid waste sites dominated by a Si-Al-Si framework, characterized in that, include: The main chemical elements, crystal structure, and phase composition of the polymers in the solid waste base were tested. Based on the main chemical elements, crystal structure, and phase composition of the solid waste aggregate, key elements were screened, and a molecular structure model was constructed. Force fields and charges were then assigned to these key elements and the molecular structure model. Among these key elements, Na is included. + Ca 2+ and Mg 2+ The molecular structure model includes Si9Al4O 36 Molecular structure; The molecular structure model is randomly dispersed in a cubic unit cell to construct an initial amorphous unit cell model and an H2O model; The initial amorphous unit cell model was combined with the H2O model to obtain a solid-liquid interface model, and the solid-liquid interface model was geometrically optimized. The geometrically optimized solid-liquid interface model is subjected to NVT equilibration to obtain a stable solid-liquid interface model. Molecular dynamics simulations were performed on the stable solid-liquid interface model to obtain relevant data, including radial distribution function, interfacial adsorption energy, axial concentration, mean square displacement, and number of hydrogen bonds.
2. The atomic-level modeling method for the solid-liquid interface of a solid waste-based polymer hydration process dominated by a Si-Al-Si framework, as described in claim 1, is characterized in that... The composition of the main chemical elements of the solid waste base polymer is tested, and the chemical elements and element ratios required for modeling are determined based on the proportion of the main chemical composition of the solid waste base polymer. The crystal structure and phase composition of the solid waste substrate polymer were tested to verify the reliability of the modeling by comparing the matching degree between the constructed amorphous unit cell model and the measured XRD diffraction peaks.
3. The method for atomic-level modeling of the solid-liquid interface in the polymer hydration process of solid waste sites dominated by a Si-Al-Si framework, as described in claim 2, is characterized in that... The Si9Al4O 36 The molecular structure is determined by the main hydration products of the geopolymer gel; The main hydration product is [SiO4]. 4- Tetrahedron and [AlO4] 5- Tetrahedrons are three-dimensional network amorphous or semi-crystalline materials formed by polymerization reactions; in this main hydration product, Si is the central atom, and Al and O atoms are connected around the central atom, and the Al atoms are connected to the Si atoms to form a network structure.
4. The atomic-level modeling method for the solid-liquid interface of a solid waste-based polymer hydration process dominated by a Si-Al-Si framework, as described in claim 1, is characterized in that... The constructed molecular structure model includes: By adding Si atoms and constructing a network of four O atoms coordinated with the Si atoms, [SiO4] is formed. 4- tetrahedron; Al atoms were respectively reacted with the [SiO4] 4- The four vertices of the tetrahedron are connected by O atoms, and three additional O atoms are connected to each Al atom to form [AlO4]. 5- The coordination environment of a tetrahedron; Using the three O atoms surrounding each Al atom as connection sites, one Si atom is attached to each of these Al atoms, and four fully coordinated O atoms are then constructed for each of these attached Si atoms to form Si9Al4O. 36 The skeletal structure was obtained, and the molecular structure model was derived.
5. The atomic-level modeling method for the solid-liquid interface of a solid waste-based polymer hydration process dominated by a Si-Al-Si framework, as described in claim 4, is characterized in that... The assignment of force fields and charges to the main element and molecular structure model includes: Select the preset force field type and the preset charge distribution method; Based on the preset force field type and preset charge distribution method, respectively, the Na + Ca 2+ and Mg 2+ and Si9Al4O 36 Molecular structure models complete the distribution of force fields and charges; Cancel the automatic calculation option and the force field type list option to complete the force field and charge assignment operation.
6. The atomic-level modeling method for the solid-liquid interface of a Si-Al-Si framework-dominated polymer hydration process in a solid waste substrate, as described in claim 1, is characterized in that... The construction of the initial amorphous unit cell model and H2O model includes: Based on the composition ratio of the main elements, input Na + Ca 2+ and Mg 2+ The number of Si9Al4O 36 The degree of polymerization of molecular chains in the molecular structure is set by pre-defined mass parameters, pre-defined density parameters, and pre-defined number of output frames to complete the distribution of the molecular structure model and the construction of the initial amorphous unit cell model; Select H2O molecules, enter the number of H2O molecules to add, and set the preset mass parameters, preset density parameters, and preset number of output frames to complete the construction of the H2O model.
7. The atomic-level modeling method for the solid-liquid interface of a solid waste-based polymer hydration process dominated by a Si-Al-Si framework, as described in claim 1, is characterized in that... The combination of the initial amorphous unit cell model and the H2O model to obtain the solid-liquid interface model includes: Ensure that the length, width, height, and angle of the H2O model are completely consistent with the settings of the initial amorphous cell model; wherein, the length and width of the initial amorphous cell model and the H2O model are both greater than a first multiple of the preset cutoff radius, and the height of the initial amorphous cell model and the H2O model are both greater than a second multiple of the preset cutoff radius; The initial amorphous unit cell model is used as the first layer, the H2O model is used as the second layer, a vacuum layer of preset thickness is added on top of the H2O model, and the first layer is selected as the matching reference to form a solid-liquid interface model.
8. The atomic-level modeling method for the solid-liquid interface of a solid waste-based polymer hydration process dominated by a Si-Al-Si framework, as described in claim 7, is characterized in that... The geometric optimization of the solid-liquid interface model includes: A preset optimization algorithm is used, and the calculation accuracy, maximum number of iterations, and force field type are set. Based on a pre-defined optimization algorithm, combined with electrostatic force calculations and van der Waals force calculations, the bond configuration and atomic charge distribution in the solid-liquid interface model are corrected to obtain a molecular structure model with lower energy.
9. The atomic-level modeling method for the solid-liquid interface of a Si-Al-Si framework-dominated polymer hydration process in a solid waste substrate, as described in claim 1, is characterized in that... The NVT balancing process for the geometrically optimized solid-liquid interface model includes: The simulation process is controlled by the NVT ensemble, and the initial velocity type, temperature, time step and total simulation duration are set. The total simulation duration is divided into the system preheating equilibrium stage and the data acquisition stage according to the preset ratio, and the system trajectory is recorded at the preset time interval. By selecting the thermostat type and force field type, and combining electrostatic force calculations and van der Waals force calculations, a stable solid-liquid interface model can be obtained.
10. The method for atomic-level modeling of the solid-liquid interface in the polymer hydration process of solid waste sites dominated by a Si-Al-Si framework, as described in claim 1, is characterized in that... The molecular dynamics simulation of the stable solid-liquid interface model yielded the following data: Based on a stable solid-liquid interface model, a cutoff radius and interval distance were set, and the characteristic peak positions of the target bonds in the stable solid-liquid interface model were obtained through radial distribution function analysis to verify the rationality of the coordination structure of the stable solid-liquid interface model; the target bonds include Si-O bonds, Al-O bonds and H2O bonds; The interfacial adsorption energy of the solid-liquid interface in the stable solid-liquid interface model was calculated to verify that the stable solid-liquid interface model conforms to the spontaneous adsorption between solid waste particles and water molecules. Axial concentration calculations were performed on the solid-liquid interface of the stable solid-liquid interface model to directly characterize the degree of directional aggregation of hydration products and the direction of the activation reaction interface of solid waste particles. The diffusion coefficient of ions was obtained by mean square displacement calculation to characterize the propulsion rate of ion migration during the polymer hydration reaction in solid waste base. Hydrogen bond analysis was used to count the number of hydrogen bonds at the solid-liquid interface in a stable solid-liquid interface model, in order to quantify the degree of hydration of the solid waste-based polymer during the hydration process.