A method for predicting geopolymer proportions and geopolymer-aggregate interface bonding properties based on molecular simulation

Abstract

The present invention belongs to the technical field of geopolymer industrial materials, and specifically is a method for predicting geopolymer proportions and geopolymer-aggregate interface bonding properties based on molecular simulation. The present invention constructs geopolymer models with different calcium contents through molecular dynamics simulation, simulates their mechanical properties, and then verifies the simulation results through experiments. This method can effectively predict the influence of raw material proportions on the mechanical properties of geopolymers, significantly reduces the time and cost required for experiments, and provides an important reference for the design and optimization of subsequent geopolymer materials. In addition, the present invention also explores the interfacial interaction between different types of aggregates and geopolymers at the molecular level by constructing interface models of geopolymers and coal gangue aggregates and granite aggregates, evaluates the degree of bonding between the two by calculating the interfacial interaction energy between geopolymers and different aggregates, and verifies it by performing splitting experiments, providing valuable guidance for the selection and application of aggregates in actual engineering.

Description

Technical Field

[0001] The present invention belongs to the technical field of resource utilization of industrial solid waste materials, and particularly relates to a method for predicting geopolymer proportion and geopolymer-aggregate interface bonding properties based on molecular simulation. Background Art

[0002] With the continued growth of the global economy and the acceleration of urbanization, the demand for cement has skyrocketed. However, the high energy consumption and emissions associated with cement production have become increasingly prominent, posing a significant challenge to sustainable development. Geopolymer, an emerging green building material, is considered a viable alternative to traditional cement. Geopolymers are primarily formed through a series of chemical reactions involving natural minerals or industrial waste rich in aluminosilicates in the presence of an alkaline activator. Their rise and application not only represents a positive response to environmental concerns but also represents an important implementation of the concept of resource recycling.

[0003] Geopolymers are widely used in building materials, solid waste treatment, and high-temperature resistant materials due to their high strength, durability, environmental friendliness, and low cost. Common raw materials for preparing geopolymers include metakaolin, circulating fluidized bed fly ash, fly ash, red mud, slag, and silica fume. However, each raw material contains varying types and amounts of oxides. Using traditional experiments based on concrete curing specifications to investigate the effects of oxide content in each solid waste material on geopolymer performance is time-consuming and costly.

[0004] To optimize the mechanical properties of geopolymers, improve construction performance, and reduce costs, a certain amount of aggregate is often added during their preparation. This helps enhance the compressive strength, flexural strength, and wear resistance of geopolymers, enabling them to better meet the requirements of various engineering structures. Numerous studies have demonstrated the environmental friendliness and economic benefits of using coal gangue and granite as aggregates. Furthermore, the addition of aggregate improves the fluidity and workability of geopolymers, facilitating construction operations and increasing efficiency. However, existing macroscopic experiments have made it difficult to assess the interaction between aggregate and geopolymer. Therefore, more sophisticated microscopic studies and simulations are needed to further analyze this process.

[0005] Molecular dynamics simulation is a computer simulation method that studies the microscopic and macroscopic properties of a system by simulating the motion trajectories of its atoms and molecules. The results can be used to predict the mechanical properties of different raw material ratios, thereby optimizing material design. Traditional building material research typically requires extensive experimental verification, which is not only time-consuming and labor-intensive, but also costly. Molecular dynamics simulation, on the other hand, allows rapid computer-generated simulations to be conducted multiple times. By comparing simulation results under different conditions, the optimal solution can be identified, significantly reducing the number and cost of conventional experiments.

[0006] The invention patent with application number CN202310410069.0 proposes a 137Cs wastewater treatment method based on molecular dynamics simulation. It uses molecular dynamics simulation to explore the process of geopolymer solidification of Cs atoms, but it is limited to the atomic level and has not been combined with practice. The invention patent with application number CN202410077340.8 proposes a method for constructing a molecular model of the interface between epoxy oligomer and phosphogypsum based on molecular dynamics simulation, but does not elaborate on how the model explains the mechanism between the material interfaces. Current research on the properties of geopolymers and their interactions with geopolymer aggregates is mostly limited to macroscopic experimental studies, and there are few studies that use molecular dynamics simulation to explore their trends and guide experiments. Summary of the Invention

[0007] To address the shortcomings of existing technologies, the present invention provides a method for predicting geopolymer proportions and geopolymer-aggregate interfacial bonding properties based on molecular simulation. This method uses molecular dynamics simulations to investigate the effects of varying raw material content on geopolymer properties, as well as the interactions between geopolymers and different aggregate types. This method not only provides a deep understanding of geopolymer properties at the atomic level, but also can be used to guide experimental raw material proportioning and design, thereby improving experimental efficiency and optimizing material properties.

[0008] In order to solve the above problems, the present invention first provides a method for optimizing the ratio of geopolymer raw materials based on molecular simulation, comprising the following steps:

[0009] (1) Selecting the sialate-siloxo structural unit commonly found in geopolymers as oligomer molecules for constructing the geopolymer model, and filling the model with a preset number of oligomer molecules and alkali cations, wherein the charge number of the alkali cations is equal to the number of oligomer molecules filled;

[0010] (2) Perform energy minimization and melt annealing equilibrium processing on the constructed geopolymer model;

[0011] (3) Perform uniaxial compression simulation on the geopolymer model with different filling amounts after equilibrium, and record the compressive strength of the geopolymer model;

[0012] (4) Designing the geopolymer raw material ratio according to the number of filled alkali cations corresponding to the compressive strength.

[0013] Furthermore, the silicon-aluminum ratio of the sialate-siloxo structural unit is 2; the alkali cations are sodium ions and / or calcium ions, the number of the oligomer small molecules filled is 136, and the total charge number of the sodium ions and calcium ions is 136;

[0014] The geopolymer raw materials include metakaolin, circulating fluidized bed fly ash and silica fume, and the amount of the circulating fluidized bed fly ash is proportional to the filling amount of the calcium ions in the geopolymer model.

[0015] Preferably, the geopolymer model component described in step (1) comprises 136 oligomer molecules, 30 calcium ions, and 76 sodium ions.

[0016] Preferably, the geopolymer model component described in step (1) comprises 136 oligomer molecules, 20 calcium ions, and 96 sodium ions.

[0017] Preferably, the geopolymer model component described in step (1) includes 136 oligomer molecules and 136 sodium ions.

[0018] The common way to build a model for molecular simulation is to use the AmorphousCell module in Materials Studio. During the modeling process, click the Amorphous Cell option to output the number of small molecules and the set density. The software will automatically determine the size of the box based on the filled values. You can also set a target box size and density, and the software will calculate the number of structural units that need to be filled. The box containing all the small molecules can be regarded as a molecular model, such as Figure 1 The black wireframe in the Geopolymer diagram is this box, and the box plus all the small molecules inside it form a model.

[0019] The purpose of constructing a box in molecular simulation is to define the spatial scope and boundary conditions of the calculation. It is a basic operation of molecular simulation. By setting an appropriate box size, boundary effects can be avoided, thereby ensuring the accuracy and reliability of the simulation results.

[0020] The box size set in the present invention is The proposed density is 2g / cm 3 , then according to the set box size and density, the number of structures that need to be filled in this example can be obtained by inputting into the software.

[0021] Furthermore, the energy minimization process uses a conjugate gradient algorithm to bring the geopolymer model to a minimum energy state; the melt annealing equilibration process includes equilibration at a temperature of 300K for 50 ps in an NVT ensemble, then equilibration in an NVT ensemble at 1500K for 500 ps, ​​and cooling from 1500K to 300K at a rate of 5K / ps; subsequently, equilibration in the NPT ensemble and NVT ensemble for 200 ps respectively;

[0022] The operation steps of the uniaxial compression simulation are as follows: uniaxial pressure is applied to the model along the z-axis direction, and the strain rate during the compression process is set to a constant strain rate. The pressure in the x and y directions is controlled to 0.

[0023] The present invention also provides a method for predicting geopolymer-aggregate interface bonding properties based on molecular simulation, comprising the following steps:

[0024] (1) Selecting the sialate-siloxo structural unit with a silicon-aluminum ratio of 2, which is common in geopolymers, as the oligomer small molecule to construct the geopolymer model, filling it with a preset number of oligomer small molecules and the same number of sodium ions;

[0025] (2) The aggregate model is constructed by selecting the mineral components with the highest content in coal gangue aggregate or granite aggregate;

[0026] (3) combining the geopolymer model in step (1) and the aggregate model in step (2) to construct a geopolymer-aggregate interface model;

[0027] (4) Energy minimization and melt annealing equilibrium treatment were performed on the constructed geopolymer-aggregate interface model;

[0028] (5) Calculate the interfacial interaction energy of the equilibrium geopolymer-aggregate interface model. The larger the absolute value of the interfacial interaction energy, the better the interfacial bonding performance.

[0029] Further, in the step 2), the mineral component with the highest content selected from the coal gangue aggregate is kaolinite, and the mineral component with the highest content selected from the granite aggregate is quartz;

[0030] The geopolymer-aggregate interface model is constructed by combining Build Layers in Materials Studio software;

[0031] The force field used in the molecular dynamics simulation was the ReaxFF force field, and the time step was 0.25 fs. The molecular dynamics simulation equilibrium process was performed in LAMMPS software.

[0032] Furthermore, the energy minimization process of the geopolymer-aggregate interface model is as follows: the geopolymer-aggregate model is geometrically optimized using a conjugate gradient algorithm; the melt annealing equilibrium process is as follows: the surface of the aggregate unit cell at the interface is minimized. The following atoms were fixed and equilibrated at 300 K in the NVT ensemble for 50 ps. The system was heated to 1500 K and equilibrated for 500 ps, ​​and then cooled to 300 K at a rate of 5 K / ps. Finally, it was equilibrated in the NPT and NVT ensembles for 200 ps, ​​respectively.

[0033] Preferably, in the geopolymer-aggregate interface model, the geopolymer portion includes 136 oligomer molecules and 136 sodium ions, and the aggregate is kaolinite, the mineral component with the highest content in coal gangue aggregate.

[0034] Preferably, in the geopolymer-aggregate interface model, the geopolymer portion includes 136 oligomer molecules and 136 sodium ions, and the aggregate is quartz, the mineral component with the highest content in granite aggregate.

[0035] Furthermore, the calculation formula of the interfacial interaction energy of the geopolymer-aggregate interface model is:

[0036] E interface =EE geopolymer -E aggregate

[0037] Where, E interface is the interfacial interaction energy between geopolymer and aggregate, expressed in Kcal / mol;

[0038] E - total potential energy of the geopolymer-aggregate interface model, in Kcal / mol;

[0039] E geopolymer is the potential energy of the geopolymer part, in Kcal / mol;

[0040] E aggregate is the potential energy of the aggregate part, with the unit of Kcal / mol.

[0041] E interface are the values ​​obtained by calculation, E and E geopolymer , E aggregate It can be obtained by writing code, where E, E geopolymer , E aggregate The calculation process is as follows: Figure 3 The interface model shown on the right has geopolymer on the top and aggregate on the bottom. The boundary between geopolymer and aggregate is determined, and the total potential energy E of the interface model is calculated. The code is used to first delete the atoms in the geopolymer part of the interface model (and the atoms above the boundary line) and calculate the potential energy E of the remaining atoms, i.e., the aggregate part. aggregate Similarly, delete the atoms of the aggregate part (and the atoms below the dividing line) to obtain the potential energy E of the geopolymer part geopolymer , the difference is E interface .

[0042] The present invention also conducted geopolymer model verification experiments, geopolymer ratio verification experiment preparation and testing, and the specific steps are as follows:

[0043] (1) Raw material processing: The metakaolin, circulating fluidized bed fly ash and silica fume were passed through a 0.075 mm square hole sieve. The sieved materials were placed in an oven and dried to constant weight.

[0044] (2) Mixing of cementitious materials: Add metakaolin, circulating fluidized bed fly ash and silica fume into a mixer and stir at low speed for 1 minute to obtain a solid mixture. Then add the alkaline activator solution and stir at high speed for 2 minutes.

[0045] (3) Curing: Pour the gelled slurry mixed in step (2) into a 40×40×40 mm mold, and use a scraper to flatten the mold surface. Cover the surface with plastic wrap, let it stand at room temperature for 24 hours, then demould and perform standard curing.

[0046] (4) Test: Take the sample cured for 7 days and conduct infinite compressive strength test with a loading rate of 2.4 kN / s. The test results are recorded as the average of three times. The calculation process of the compressive strength of the test block cube is as follows:

[0047]

[0048] Where, f cc -compressive strength of cubic specimen (MPa); F-failure load of cubic specimen (N); A-pressure bearing area of ​​cubic specimen (mm 2 ).

[0049] The experimental preparation and testing characteristics of the geopolymer-aggregate interface bonding performance verification experiment are as follows:

[0050] (1) Raw material processing: pass the metakaolin and silica fume through a 0.075 mm square hole sieve, and place the sieved materials in an oven to dry to constant weight.

[0051] (2) Aggregate pretreatment: Cut the coal gangue aggregate and granite aggregate into 40×40×20mm cuboids.

[0052] (3) Mixing of cementitious materials: Add metakaolin and silica fume into a mixer and stir at low speed for 1 minute to obtain a solid mixture. Then add the alkaline activator solution and stir at high speed for 2 minutes.

[0053] (4) Curing: Place the aggregate test block cut in step (2) on one side of a 40×40×40 mm mold, add the cementitious slurry mixed in step (3) to the other side, and use a scraper to flatten the mold surface. Cover the surface with plastic wrap, let it stand at room temperature for 24 h, then demould and perform standard curing.

[0054] (5) Test: Take the specimens cured for 7 days and conduct splitting tensile test with a loading rate of 1.0 KN / s. The test results are recorded as the average of three times. The splitting strength of the specimen is calculated as follows:

[0055]

[0056] Where, f ts - splitting tensile strength (MPa); F- specimen failure load (N); A- specimen splitting surface area (mm 2 ).

[0057] Preferably, the components prepared in the geopolymer-aggregate interface bonding performance verification experiment include 70 parts by weight of metakaolin and 30 parts of silica fume, and the aggregate is coal gangue aggregate.

[0058] Preferably, the components prepared in the geopolymer-aggregate interface bonding performance verification experiment include 70 parts by weight of metakaolin and 30 parts of silica fume, and the aggregate is granite aggregate.

[0059] The present invention also provides a method for preparing a geopolymer, which first adopts the above-mentioned method to obtain an optimized ratio of geopolymer raw materials, and then mixes and cures the geopolymer raw materials; specifically, it comprises:

[0060] (1) Raw material processing: According to the ratio of geopolymer raw materials, metakaolin, circulating fluidized bed fly ash and silica fume are passed through a 0.075 mm square hole sieve, and the sieved materials are placed in an oven and dried to constant weight;

[0061] (2) Mixing of gelled slurry: Add metakaolin, circulating fluidized bed fly ash and silica fume into a blender and stir for 1 minute to obtain a solid mixture, then add the alkaline activator solution and stir for 2 minutes to obtain a gelled slurry;

[0062] (3) Curing: Pour the gelled slurry mixed in step (2) into a mold, cover the surface with plastic wrap, let it stand at room temperature for not less than 24 hours, then demould and perform standard curing to obtain a geopolymer.

[0063] Furthermore, the geopolymer comprises, by weight, 40-70 parts of metakaolin, 0-30 parts of circulating fluidized bed fly ash, and 30 parts of silica fume; wherein the total of the metakaolin, circulating fluidized bed fly ash, and silica fume is 100 parts; and the mass ratio of the total of the metakaolin, circulating fluidized bed fly ash, and silica fume to the alkaline activator solution is 100:40;

[0064] The composition of the metakaolin includes SiO2 51.72%, Al2O3 45.11%, CaO0.11%, Fe2O3 1.04%, K2O 0.78%, SO3 0.08% and TiO2 0.2% by mass fraction;

[0065] The composition of the circulating fluidized bed fly ash includes SiO2 34.41%, Al2O3 24.57%, CaO2 0.88%, MgO 1.26%, Fe2O3 5.15%, K2O 1.16%, SO3 9.6% and TiO2 1.17% by mass;

[0066] The silica fume comprises SiO2 95.53%, Al2O3 0.46%, CaO 1.04%, Fe2O3 0.11%, MgO 0.34%, SO3 0.17% and TiO2 0.01% by mass fraction;

[0067] The alkaline activator solution is a mixed solution of sodium silicate solution and sodium hydroxide powder, wherein the sodium silicate solution has a SiO2 content of 26.2%, a Na2O content of 8.3%, a modulus of 3.2, a Baume degree of 40, and a sodium hydroxide purity of 99%. The modulus of the prepared alkaline activator solution is 1.5.

[0068] Preferably, the geopolymer raw material ratio is as follows:

[0069] Preferably, the components prepared in the geopolymer verification experiment include 40 parts by weight of metakaolin, 30 parts of circulating fluidized bed fly ash, and 30 parts of silica fume.

[0070] Preferably, the components prepared in the geopolymer verification experiment include 50 parts by weight of metakaolin, 20 parts of circulating fluidized bed fly ash, and 30 parts of silica fume.

[0071] Preferably, the components prepared in the geopolymer verification experiment include 60 parts by weight of metakaolin, 10 parts of circulating fluidized bed fly ash, and 30 parts of silica fume.

[0072] Preferably, the components prepared in the geopolymer verification experiment include 70 parts by weight of metakaolin, 0 parts of circulating fluidized bed fly ash, and 30 parts of silica fume.

[0073] The standard curing temperature is 20±2°C and the humidity is ≥95%.

[0074] This paper constructs geopolymer models with varying calcium contents through molecular dynamics simulations, simulates their mechanical properties, and then verifies the simulation results through experiments. This method can effectively predict the impact of raw material ratios on the mechanical properties of geopolymers, significantly reducing the time and cost required for experiments, and providing an important reference for the design and optimization of subsequent geopolymer materials. Furthermore, by constructing interface models between geopolymers and coal gangue and granite aggregates, the present invention explores the interfacial interactions between different types of aggregates and geopolymers at the molecular level. The degree of bonding between geopolymers and different aggregates is assessed by calculating the interfacial interaction energy between the geopolymers and the different aggregates, and is verified through splitting experiments. This provides valuable guidance for the selection and application of aggregates in practical engineering projects.

[0075] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0076] 1. The model of the present invention is simple to construct. By constructing a geopolymer model and a geopolymer-aggregate interface model, the microscopic properties of the material can be explored at the atomic level, and the influence of the raw material ratio on the mechanical properties of the geopolymer can be reflected to a certain extent. The prediction results of molecular simulation can provide guidance for the design of the experiment. With the help of the results obtained by simulation, the content of circulating fluidized bed fly ash can be controlled in the experiment, reducing the blindness and trial and error costs of the experiment. At the same time, the degree of bonding between geopolymer and aggregate can be explored by adjusting different types of aggregates, thereby providing a certain reference for the selection of aggregate types in the experiment. The experimental results can also provide new research directions and ideas for molecular simulation. The two complement each other, so that the characteristics of the material can be better understood.

[0077] 2. The present invention utilizes computer simulation technology, which is simple to operate and has a short simulation cycle, greatly simplifying the problems of long traditional experimental cycles and high costs. It provides a new prediction and optimization approach for exploring the influence of raw material ratios on the compressive strength of geopolymers, and the simulation data is in good agreement with the experiments.

[0078] 3. The use of molecular dynamics simulation can largely make up for the shortcomings of experiments. For aspects that traditional experiments cannot cover, such as the characteristics and differentiation of aggregate structure, molecular dynamics simulation can intuitively and clearly reflect its characteristics, which has certain guiding significance for the types of aggregates in subsequent actual projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] Figure 1 Schematic diagram of the process built for the geopolymer model.

[0080] Figure 2Schematic diagram of the constructed geopolymer model, wherein (a) is the geopolymer model constructed in Example 1, (b) is the geopolymer model constructed in Example 2, (c) is the geopolymer model constructed in Example 3, and (d) is the geopolymer model constructed in Example 4.

[0081] Figure 3 Schematic diagram of the process flow constructed for the geopolymer-aggregate model.

[0082] Figure 4 Schematic diagram of uniaxial compression simulation of geopolymer model.

[0083] Figure 5 Schematic diagram of the interface interaction energy composition of the geopolymer-aggregate model. DETAILED DESCRIPTION

[0084] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely for the purpose of explaining the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.

[0085] Simulation Example 1

[0086] like Figure 1 As shown, the method for constructing a geopolymer model based on molecular dynamics simulation in the present invention is carried out in the following steps:

[0087] (1) Constructing the geopolymer model: The sialate-siloxo structural unit with a silicon-aluminum ratio of 2, which is common in geopolymers, was selected as the oligomer small molecule for constructing the geopolymer. 136 oligomer small molecules, 40 calcium ions, and 56 sodium ions were filled in the model according to the number, and the starting density was set to 2 g / cm 3 , and obtain the initial geopolymer model. Among them, the oligomer small molecule is the sialate-siloxo structural unit, which is a silicate structural unit and an inorganic small molecule. The specific molecular structure is shown in Figure 1 Left picture.

[0088] (2) Equilibration setup: First, energy minimization was performed using the conjugate gradient algorithm to ensure that the system reached the lowest energy state. The melt annealing equilibration process included equilibrating the model at 300 K for 50 ps in the NVT ensemble to ensure basic density stability. The model was then equilibrated in the NVT ensemble at 1500 K for 500 ps and cooled from 1500 K to 300 K at a rate of 5 K / ps. Subsequently, the model was equilibrated in the NPT ensemble and the NVT ensemble for 200 ps each.

[0089] (3) Compressive strength: The compressive strength of the geopolymer model is measured by applying uniaxial pressure to the model along the z-axis. The strain rate during compression is set to a constant engineering strain rate. The NPT ensemble was used at a temperature of 300 K, and the pressure in the x and y directions was controlled to be zero.

[0090] Simulation Example 2

[0091] The operation process is the same as that of simulation 1, except that 136 oligomer molecules, 30 calcium ions, and 76 sodium ions are filled in according to the quantity when constructing the geopolymer model.

[0092] Simulation Example 3

[0093] The operation process is the same as that of Simulation Example 1, except that 136 oligomer molecules, 20 calcium ions, and 96 sodium ions are filled in according to the quantity when constructing the geopolymer model.

[0094] Simulation Example 4

[0095] The operation process is the same as that of Simulation Example 1, except that 136 oligomer molecules and 136 sodium ions are filled in according to the quantity when constructing the geopolymer model.

[0096] On the other hand, see Figure 3 The method for constructing a geopolymer-aggregate interface model based on molecular dynamics simulation of the present invention is carried out in the following steps:

[0097] Simulation Example 5

[0098] (1) Constructing a geopolymer model: The sialate-siloxo structural unit with a silicon-aluminum ratio of 2, which is common in geopolymers, was selected as the oligomer small molecule for constructing the geopolymer. 136 oligomer small molecules and 136 sodium ions were filled in the model, and the starting density was set to 2 g / cm 3 , and obtain the initial geopolymer model.

[0099] (2) Constructing the aggregate molecular model: Kaolinite, the mineral component with the highest content in coal gangue aggregate, was selected as the aggregate unit cell. The kaolinite unit cell was cut along the commonly used crystal plane (001), and the aggregate unit cell was expanded to a size close to that of the geopolymer unit cell.

[0100] (3) Combined model: The geopolymer model constructed in step (1) and the aggregate model constructed in step (2) are combined using the Build Layer module in Materials Studio software to construct a geopolymer-gangue aggregate interface model.

[0101] (4) Equilibrium setting: First, perform energy minimization and use the conjugate gradient algorithm to perform geometric optimization on the geopolymer-gangue aggregate model to ensure that the system reaches the lowest energy state. The melt annealing equilibrium process includes: The following atoms were fixed to better explore the reactions at the composite interface. The system was equilibrated at 300 K for 50 ps in the NVT ensemble. The system was then heated to 1500 K for 500 ps to accelerate polymerization. The system was then cooled at a rate of 5 K / ps until the temperature dropped to 300 K. Finally, the system was equilibrated in both the NPT and NVT ensembles for 200 ps.

[0102] (5)Interface interaction energy: E interface =EE geopolymer -E aggregate

[0103] Where E interface -Interfacial interaction energy between geopolymer and aggregate (Kcal / mol);

[0104] E - total energy of geopolymer-aggregate interface model (Kcal / mol);

[0105] E geopolymer -Potential energy of the geopolymer fraction (Kcal / mol);

[0106] E aggregate -Potential energy of the aggregate fraction (Kcal / mol).

[0107] Simulation Example 6

[0108] The simulation method is the same as that of Simulation Example 5, except that quartz, the mineral component with the highest content in granite aggregate, is selected as the aggregate unit cell when constructing the aggregate molecular model.

[0109] In addition to the molecular dynamics simulation, the present invention also conducted geopolymer strength and geopolymer-aggregate interface bond strength verification experiments. The specific operation method of the geopolymer strength verification experiment is as follows:

[0110] Experimental Example 1

[0111] (1) Raw material processing: The metakaolin, circulating fluidized bed fly ash and silica fume were passed through a 0.075 mm square hole sieve. The sieved materials were placed in an oven and dried to constant weight.

[0112] (2) Mixing of cementitious materials: Add metakaolin, circulating fluidized bed fly ash, and silica fume into a mixer at a mass ratio of 40 parts, 30 parts, and 30 parts, and stir at a low speed for 1 minute to obtain a solid mixture. Then add the alkaline activator solution and stir at a high speed for 2 minutes to obtain a cementitious slurry.

[0113] (3) Curing: Pour the gelled slurry mixed in step (2) into a 40×40×40 mm mold, and use a scraper to flatten the mold surface. Cover the surface with plastic wrap and let it stand at room temperature for 24 hours. After 24 hours, demould and perform standard curing.

[0114] (4) Test: Take the sample cured for 7 days and conduct infinite compressive strength test with a loading rate of 2.4 kN / s. The test results are recorded as the average of three times. The calculation process of the compressive strength of the test block cube is as follows:

[0115]

[0116] Where, f cc - cubic specimen compressive strength (MPa); F- specimen failure load (N); A- specimen pressure bearing area (mm 2 ).

[0117] Experimental Example 2

[0118] The preparation method is the same as that of Example 1, except that the mass proportions of kaolin, circulating fluidized bed fly ash, and silica fume are 50 parts, 20 parts, and 30 parts, respectively.

[0119] Experimental Example 3

[0120] The preparation method is the same as that of Example 1, except that the mass proportions of kaolin, circulating fluidized bed fly ash, and silica fume are 60 parts, 10 parts, and 30 parts, respectively.

[0121] Experimental Example 4

[0122] The preparation method is the same as that of Example 1, except that the mass fractions of kaolin, circulating fluidized bed fly ash, and silica fume are 70 parts, 0 part, and 30 parts, respectively.

[0123] The specific operation method of the geopolymer-aggregate interface bond strength verification experiment is as follows:

[0124] Experimental Example 5

[0125] (1) Raw material processing: pass the metakaolin and silica fume through a 0.075 mm square hole sieve, and place the sieved materials in an oven to dry to constant weight.

[0126] (2) Mixing of cementitious materials: Add metakaolin and silica fume into a mixer and stir at low speed for 1 minute to obtain a solid mixture. Then add the alkaline activator solution and stir at high speed for 2 minutes.

[0127] (3) Aggregate processing: Cut the gangue aggregate into 40×40×20mm cuboids

[0128] (4) Curing: Place the aggregate test block cut in step (3) on one side of a 40×40×40 mm mold, add the mixed cementitious slurry to the other side, and use a scraper to flatten the mold surface. Cover the surface with plastic wrap and let it stand at room temperature for 24 hours. After 24 hours, demould and perform standard curing.

[0129] (5) Test: Take the sample cured for 7 days and conduct splitting tensile test with a loading rate of 1.0 KN / s. The test results are recorded as the average of three times. The calculation process of the compressive strength of the test block cube is as follows:

[0130] Where, f ts - splitting tensile strength (MPa); F- specimen failure load (N); A- specimen splitting surface area (mm 2 ).

[0131] Experimental Example 6

[0132] The preparation method is the same as that of Example 5, except that granite aggregate is used as the aggregate.

[0133] Analysis of results from a molecular simulation-based method for predicting geopolymer mix ratios and geopolymer-aggregate interface bonding properties:

[0134] 1. Geopolymer Molecular Dynamics Simulation Design and Analysis

[0135] Geopolymers were first proposed and extensively studied by J. Davidovits in 1978. Their unique three-dimensional network structure is formed by the polymerization of numerous oligomeric molecules. Geopolymer oligomers can be classified according to their silicon-to-aluminum ratio into sialate units (Si / Al = 1), sialate-siloxo units (Si / Al = 2), and sialate-disiloxo units (Si / Al = 3). Therefore, the present invention uses sialate-siloxo units, which have a common silicon-to-aluminum ratio (atomic molar ratio) of 2, as the oligomeric units for geopolymer construction. By controlling the number of oligomeric molecules in each model and adjusting the ratio of calcium ions to sodium ions, the resulting geopolymer model components are shown in Table 1. In molecular dynamics simulations, the total charge of anions and cations must be equal. Therefore, in the molecular simulation setup, the number of sialate-siloxo units (i.e., the anionic charge) is first maintained constant. The ratio of sodium ions to calcium ions is then calculated to ensure a total cationic charge of 136.

[0136] Table 1 Summary of geopolymer model components

[0137]

[0138] The four equilibrium geopolymer models above are respectively Figure 4 Uniaxial compression simulations were performed with the same simulation settings for each group, and the resulting compressive strengths are shown in Table 2.

[0139] Table 2 Summary of simulated uniaxial compression strength of geopolymers

[0140]

[0141] 2. Molecular dynamics simulation design and analysis of geopolymer-aggregate interface bonding performance

[0142] This simulation used two common aggregates, gangue and granite. However, due to their complex mineral composition, it is difficult to construct a model that fully reflects their true complex state and properties at the molecular scale. Therefore, the mineral component with the highest content is usually selected to represent the aggregate to simplify the model and highlight its key characteristics, thereby more accurately studying its performance and behavior. Although this operation simplifies the complexity of the aggregate, it can still effectively reflect its key characteristics and interactions in the simulation. Therefore, for the gangue aggregate and granite aggregate, kaolinite and quartz, the two mineral components with the highest content, were selected as representatives, respectively. Both groups of geopolymers were filled with the same amount of oligomer small molecules and sodium ions. The specific configuration is shown in Table 3.

[0143] Table 3 Summary of components of geopolymer-aggregate interface model

[0144]

[0145] Molecular dynamics simulations were performed on the two groups of geopolymer-aggregate interface models mentioned above, and the interfacial interaction energy between the geopolymer and the aggregate was calculated. The calculation results are summarized in Table 4.

[0146] Table 4 Interfacial interaction energy of geopolymer-aggregate interface model

[0147]

[0148] The magnitude of interfacial interaction energy directly reflects the bond strength between geopolymer and aggregate. This study established interfacial models for geopolymer, gangue aggregate, and granite aggregate, and calculated the interfacial interaction energy between these two aggregates. The results, shown in Table 4, show that the interfacial interaction energy for both aggregates is negative, indicating mutual attraction between the geopolymer and these two aggregates. The absolute value of the interfacial interaction energy for granite is greater than that for gangue, indicating a stronger bond between the granite and geopolymer. Therefore, by simulating and calculating the interfacial interaction energy between geopolymer and aggregate, we can predict the bond strength between different aggregate types and geopolymer, providing a theoretical basis for aggregate selection in practical engineering projects.

[0149] 3. Geopolymer Verification Test Design and Analysis

[0150] In the geopolymer verification experiment, metakaolin (MK), circulating fluidized bed fly ash (CFBFA), and silica fume (SF) were selected as raw materials for preparing geopolymers. The alkaline activator was a mixed solution of sodium silicate solution and sodium hydroxide powder. Metakaolin is the most commonly used raw material for preparing geopolymers. Circulating fluidized bed fly ash is a by-product of circulating fluidized bed boilers in power plants. Its application in building materials can effectively reduce waste landfills and achieve resource recycling. Since the geopolymer model in this molecular dynamics simulation uses oligomers with a silicon-aluminum ratio of 2, the silicon-aluminum ratio condition of 2 must be met in the verification experiment. A higher proportion of silica fume is added to supplement the silicon source. The proportion of oxides in the geopolymer raw materials is shown in Table 5.

[0151] Table 5 Ratio of raw material oxides

[0152]

[0153] It can be seen from Table 5 that the calcium oxide content in metakaolin and silica fume is extremely small and can be ignored. Therefore, in this experiment, circulating fluidized bed fly ash can be regarded as the only source of calcium content. On this basis, the ratio of the three raw materials of metakaolin, circulating fluidized bed fly ash and silica fume is adjusted according to the molecular dynamics simulation parameter settings. The specific ratios of the verification experiment are shown in Table 6.

[0154] Table 6 Summary of geopolymer model components

[0155]

[0156] According to the four experimental mix proportions designed in Table 6, geopolymer slurry specimens were prepared. The geopolymer specimens obtained from the experiment were subjected to standard curing. The infinite compressive strength was tested after 7 days of curing. The test results are shown in Table 7.

[0157] Table 7 Summary of 7d compressive strength of experimental geopolymers

[0158]

[0159] Combining molecular dynamics simulations (Table 2) with experimental results (Table 7), it can be found that the compressive strength trends for the four proposed mixes are consistent between the simulations and experiments. With increasing circulating fluidized bed fly ash content (calcium ion content), the compressive strength increases, indicating that calcium content has a certain enhancing effect on improving the mechanical strength of geopolymers, verifying the good agreement between the experimental and molecular dynamics simulation results. Therefore, the molecular dynamics simulations of the present invention can, to a certain extent, reflect the mechanical properties of different raw material mixes. Furthermore, by calculating the specific silicon-aluminum ratio and calcium-silicon ratio in the experiment, the corresponding parameters of the molecular dynamics model can be adjusted to predict mechanical properties and optimize experimental mixes, greatly saving time and experimental costs.

[0160] 4. Design and analysis of geopolymer-aggregate interface bond verification test

[0161] In the geopolymer-aggregate interface bonding verification experiment, in order to better explore the influence of aggregate type on the geopolymer-aggregate interface bonding performance, the geopolymer ratio was controlled to be the same in this example. Ratio 4 in Table 6 was selected as the geopolymer ratio in the geopolymer-aggregate interface verification experiment. Splitting tensile tests were performed on samples cured for 7 days. The test results are shown in Table 8.

[0162] Table 8 Splitting tensile strength of geopolymer-aggregate specimens

[0163]

[0164] During the splitting tensile test, cracks were observed to propagate along the interface between the geopolymer and aggregate, ultimately causing failure at the interface. Since the main components of granite aggregate and gangue aggregate are quartz and kaolinite, respectively, the strength of granite aggregate is generally higher than that of gangue aggregate. Higher aggregate strength helps improve the overall strength of the composite material. Comparing the interfacial interaction energy and splitting tensile strength results of the geopolymer-aggregate interface model in Table 4 and Table 8, it can be found that the simulated interfacial interaction energy and splitting tensile strength test results both indicate that granite aggregate exhibits certain advantages in bonding performance with geopolymer. This demonstrates that the geopolymer-aggregate interface model constructed in this invention is scientifically reasonable and has important guiding value for practical research.

[0165] It's undeniable that both molecular simulation and experiments have limitations. Molecular simulation cannot fully simulate the actual state of experimental raw materials, while experiments may be subject to errors due to factors such as test conditions. However, the predictions from molecular simulation can provide guidance for experimental design. For example, in this example, raw material ratio and aggregate type are both key factors affecting geopolymer performance. By adjusting the calcium ion content in the model, it was found that calcium content has a certain positive effect on the compressive strength of the geopolymer. Therefore, using the simulation results, the content of circulating fluidized bed fly ash can be controlled in experiments, reducing experimental blindness and trial-and-error costs. Furthermore, by adjusting different types of aggregate, the degree of bonding between geopolymer and aggregate can be explored, providing a reference for the selection of aggregate types in experiments. Experimental results can also provide new research directions and ideas for molecular simulation. The two complement each other, thereby better understanding the properties of materials. Through molecular dynamics simulation technology, the present invention can predict the strength of geopolymers under different raw material ratios and evaluate the degree of interfacial bonding between geopolymers and different types of aggregates. This method can provide a reference for raw material selection and performance optimization in the design and application of geopolymer materials.

[0166] It will be easily understood by those skilled in the art that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for optimizing the ratio of geopolymer raw materials based on molecular simulation, characterized in that: The following steps are involved: (1) Selecting the sialate-siloxo structural unit of the geopolymer as the oligomer small molecule for constructing the geopolymer model, filling it with a preset number of oligomer small molecules and alkali cations, wherein the charge number of the alkali cations is equal to the number of oligomer small molecules filled; (2) Perform energy minimization and melt annealing equilibrium processing on the constructed geopolymer model; (3) Perform uniaxial compression simulation on the geopolymer model with different filling amounts after equilibrium, and record the compressive strength of the geopolymer model; (4) Designing the geopolymer raw material ratio according to the number of alkali cations filled corresponding to the compressive strength; The alkali cations are sodium ions and calcium ions, the number of the oligomer molecules filled is 136, and the total charge number of the sodium ions and calcium ions is 136; The geopolymer raw materials include metakaolin, circulating fluidized bed fly ash and silica fume, and the amount of the circulating fluidized bed fly ash is proportional to the filling amount of the calcium ions in the geopolymer model; The energy minimization process uses a conjugate gradient algorithm to make the geopolymer model reach the lowest energy state; The melt annealing equilibration process includes equilibration at a temperature of 300K in the NVT ensemble for 50ps, equilibration in the NVT ensemble at 1500K for 500ps, and cooling from 1500K to 300K at a rate of 5K / ps; then, equilibration in the NPT ensemble and NVT ensemble for 200ps respectively; The operation steps of the uniaxial compression simulation are as follows: applying uniaxial pressure to the model along the z-axis direction, setting the strain rate during the compression process to a constant strain rate of 0.01 Å / fs, and controlling the pressure in the x and y directions to 0.

2. A method for evaluating geopolymer-aggregate interface bonding performance based on molecular simulation, characterized in that: The following steps are involved: (1) The sialate-siloxo structural unit of the geopolymer was selected as the oligomer small molecule to construct the geopolymer model, and a preset number of oligomer small molecules and the same number of sodium ions were filled in; (2) Select the mineral components with the highest content in coal gangue aggregate or granite aggregate to construct the aggregate model; (3) combining the geopolymer model in step (1) and the aggregate model in step (2) to construct a geopolymer-aggregate interface model; (4) Perform energy minimization and melt annealing equilibrium processing on the constructed geopolymer-aggregate interface model; (5) Calculate the interfacial interaction energy of the geopolymer-aggregate interface model after equilibrium. The larger the absolute value of the interfacial interaction energy, the better the interfacial bonding performance. In step 2), the mineral component with the highest content selected from the gangue aggregate is kaolinite, and the mineral component with the highest content selected from the granite aggregate is quartz; The geopolymer-aggregate interface model is constructed by combining Build Layers in Materials Studio software; The energy minimization process and melt annealing equilibrium process were both performed in LAMMPS software, and the force field selected was ReaxFF force field with a time step of 0.25 fs; The energy minimization process of the geopolymer-aggregate interface model is as follows: using a conjugate gradient algorithm to perform geometric optimization on the geopolymer-aggregate model; The melt annealing equilibration process is as follows: atoms below 5Å from the surface of the interface aggregate unit cell are fixed, equilibrated at 300K for 50ps in the NVT ensemble, the system is heated to 1500K for 500ps, and then cooled to 300K at a rate of 5K / ps; finally, equilibrated in the NPT ensemble and NVT ensemble for 200ps respectively; In step 5), the calculation formula of the interfacial interaction energy of the geopolymer-aggregate interface model is: ， Where, is the interfacial interaction energy between geopolymer and aggregate, expressed in Kcal / mol; is the total potential energy of the geopolymer-aggregate interface model, in Kcal / mol; is the potential energy of the geopolymer part, in Kcal / mol; is the potential energy of the aggregate part, with the unit of Kcal / mol.

3. A method for preparing a geopolymer, characterized in that: The method according to claim 1 is used to obtain an optimized ratio of geopolymer raw materials, and then the geopolymer raw materials are mixed and cured; specifically comprising: (1) Raw material processing: According to the ratio of geopolymer raw materials, metakaolin, circulating fluidized bed fly ash and silica fume are passed through a 0.075 mm square hole sieve. The sieved materials are placed in an oven and dried to constant weight; (2) Mixing of cementitious slurry: Add metakaolin, circulating fluidized bed fly ash and silica fume into a mixer and stir for 1 minute to obtain a solid mixture. Then add the alkaline activator solution and stir for 2 minutes to obtain a cementitious slurry. (3) Curing: Pour the gelling slurry mixed in step (2) into the mold, cover the surface with plastic wrap, let it stand at room temperature for not less than 24 hours, then demould and perform standard curing to obtain the geopolymer.

4. The preparation method according to claim 3, characterized in that The geopolymer comprises, by weight, 40-70 parts of metakaolin, 0-30 parts of circulating fluidized bed fly ash, and 30 parts of silica fume; wherein the total of the metakaolin, circulating fluidized bed fly ash, and silica fume is 100 parts; and the mass ratio of the total of the metakaolin, circulating fluidized bed fly ash, and silica fume to the alkaline activator solution is 100:40; The composition of the metakaolin includes SiO2 51.72%, Al2O3 45.11%, CaO 0.11%, Fe2O3 1.04%, K2O 0.78%, SO3 0.08% and TiO2 0.2% by mass fraction; The composition of the circulating fluidized bed fly ash includes SiO2 34.41%, Al2O3 24.57%, CaO20.88%, MgO 1.26%, Fe2O3 5.15%, K2O 1.16%, SO3 9.6% and TiO2 1.17% by mass; The composition of the silica fume includes SiO2 95.53%, Al2O3 0.46%, CaO 1.04%, Fe2O3 0.11%, MgO 0.34%, SO3 0.17% and TiO2 0.01% by mass; The alkaline activator solution is a mixed solution of sodium silicate solution and sodium hydroxide powder, wherein the sodium silicate solution has a SiO2 content of 26.2%, a Na2O content of 8.3%, a modulus of 3.2, a Baume degree of 40, and a sodium hydroxide purity of 99%, wherein the modulus of the prepared alkaline activator mixed solution is 1.5; The standard curing temperature is 20°C ± 2°C and the humidity is ≥ 95%.

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