Construction system of gas-liquid two-phase molecular simulation system of hydrate promoter

Abstract

The application discloses a construction system of a hydrate promoter gas-liquid two-phase molecular simulation system, which comprises a structure generation unit, a partition construction unit and a gas-liquid splicing unit.

Description

Technical Field

[0001] This application relates to the technical field of computational materials science, and in particular to a system for constructing a gas-liquid two-phase molecular simulation system for hydrate promoters. Background Technology

[0002] Gas hydrates, also known as cage-like hydrates, are non-stoichiometric crystalline compounds formed by the self-assembly of water molecules through a hydrogen bond network, creating a porous cage-like framework structure (such as cubic sI type or face-centered cubic sII type). This cage-like framework structure (also known as hydrate cages) can trap gas molecules. This unique hydrate cage endows gas hydrates with extremely high gas storage density: under standard conditions (273 K, 101.3 kPa), 1 volume of hydrate can store the equivalent of 160-180 volumes of gas. This characteristic makes gas hydrates have broad application potential in the field of energy storage and transportation. In the context of the clean energy transition, gas hydrates are not only considered as potential carriers for the safe storage and transportation of hydrogen and natural gas, but can also be used for CO2 capture and storage technologies, which is of great significance for my country to achieve its "dual carbon" goals.

[0003] The nucleation and growth of pure gas hydrates are limited by harsh thermodynamic and kinetic conditions. Typical phase equilibrium lines require low temperatures (<250 K) and high pressures (>30 MPa), resulting in high costs for large-scale applications. To make hydrate formation conditions more flexible and facilitate commercial applications, researchers have extensively explored and introduced highly efficient hydrate promoters, including thermodynamic promoters that lower the temperature and pressure thresholds for hydrate formation (such as tetrahydrofuran (THF), propylene oxide, or methylcyclohexane), kinetic promoters that accelerate hydrate nucleation or growth rates (such as surfactants like sodium dodecyl sulfate or nanoparticles), and composite dual-effect promoters that combine thermodynamic and kinetic promotion functions (such as cyclopentane, 1,3-dioxolane (DIOX)). While hydrate promoters exhibit superior performance in promoting the nucleation and growth of gas hydrates, screening, designing, and optimizing them experimentally presents numerous challenges. The workload is immense, requiring the evaluation of the synergistic effects of thousands of candidates (such as organic molecules, inorganic molecules, surfactants, bio-based polymers, and nanoparticles) on gas hydrate growth rates and storage capacity under multivariate conditions (temperature, pressure, concentration, etc.). Furthermore, the experimental methods have high barriers to entry in synthesis and operation; different promoters require customized synthetic routes, resulting in poor adaptability. Moreover, technicians need diverse professional skills, and improper operation can easily introduce impurities that affect experimental results, leading to poor reproducibility. Existing molecular dynamics simulation methods primarily focus on the microscopic mechanisms of specific systems to reveal the microscopic mechanisms of hydrate nucleation, growth, and dissociation. Current simulation methods have limited ability to construct molecular models of promoters and are not conducive to constructing complex multi-charged ionized promoters, limiting the types of promoters that can be analyzed and potentially leading to time-consuming simulation system construction and poor applicability. Summary of the Invention

[0004] This application provides a system for constructing a gas-liquid two-phase molecular simulation system for hydrate promoters, comprising: The structure generation unit is used to generate an optimized molecular structure of the accelerator based on its chemical composition and molecular structure; wherein the optimized molecular structure of the accelerator carries the charge distribution results. A partitioned construction unit is used to construct an empty gas box with a first predetermined volume and an empty aqueous solution box with a second predetermined volume; inserting a first predetermined number of gas molecules into the empty gas box to obtain a filled gas box; inserting a second predetermined number of optimized accelerator molecules and a third predetermined number of water molecules into the empty aqueous solution box to obtain a filled aqueous solution box; and The gas-liquid splicing unit is used to splice a filled gas box and a filled aqueous solution box to obtain a gas-liquid two-phase molecular simulation system.

[0005] Furthermore, the structure generation unit includes: The molecular acquisition module is used to acquire the chemical composition and molecular structure of the promoter molecule to be evaluated; The structure drawing module is used to draw an initial structural model based on the chemical composition and molecular structure of the accelerator molecule to be evaluated. The charge generation module is used to generate the charge parameters of charged groups based on the drawn initial structural model; The structural fragmentation module is used to split the molecular structure of the promoter into multiple structural fragments based on the charge parameters of the charged groups and the segmentation generation strategy. The structural fragment splicing module is used to splice each structural fragment at its endpoints to obtain the optimized molecular structure of the promoter.

[0006] Furthermore, the split structure fragment module includes: The charge allocation submodule is used to allocate the charge when the number of charges of a charged group is greater than 2. The splitting submodule is used to split the molecular structure of the promoter into multiple structural fragments based on the distribution of charge, wherein the charge of each structural fragment is less than or equal to 2.

[0007] Furthermore, the partitioning construction unit includes: An aqueous solution box design module is used to determine the size of an empty aqueous solution box based on the size of the generated hydrate cell and the number of generated hydrate cages; wherein, the size of the empty aqueous solution box includes the length extending along a first direction, the width extending along a second direction, and the depth extending along a third direction. A gas box design module is used to determine the dimensions of an empty gas box based on the dimensions of an empty aqueous solution box; wherein the length and width of the empty gas box are equal to the length and width of the empty aqueous solution box.

[0008] Furthermore, the partitioning construction unit also includes: The first insertion module is used to insert a second predetermined number of optimized molecules of accelerator into an empty aqueous solution box, with pores formed between adjacent optimized accelerator molecules. The second insertion module is used to insert water molecules into the pores to obtain a filled aqueous solution box.

[0009] Furthermore, the gas-liquid splicing unit includes: The gas-liquid splicing module is used to place a filled aqueous solution box between two gas boxes. The filled gas boxes and aqueous solution boxes are arranged and spliced ​​sequentially along a third direction, with a predetermined gap reserved between adjacent boxes.

[0010] Furthermore, the system also includes: A molecular quantity unit is defined, which is used to determine a first set number of gas molecules, a second set number of optimized promoter molecules, and a third set number of water molecules based on simulated temperature, pressure, and promoter concentration, hydrate cell size, and the number of hydrate cages generated.

[0011] Furthermore, the system also includes: The force field parameter matching unit is used to match the corresponding force field parameters for the gas molecules, promoter molecules, and water molecules contained in the gas-liquid two-phase molecular simulation system based on the gas molecule force field model, the promoter molecule force field model, and the water molecule force field model; wherein, the force field parameters include the collision radius and the potential well depth; The computational unit is used to calculate the diffusion coefficient, solubility, and hydrate melting point of the gas-liquid two-phase molecular simulation system after matching the force field parameters. The optimized force field parameter unit is used to compare the calculated values ​​of diffusion coefficient, solubility, and hydrate melting point with experimental values, and optimize the matched force field parameters based on the comparison results.

[0012] This application provides an electronic device, which includes a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, it implements the construction system of the hydrate promoter gas-liquid two-phase molecular simulation system as described above.

[0013] This application provides a computer-readable storage medium storing computer program instructions. When executed by a processor, the computer program instructions implement the construction system of the hydrate promoter gas-liquid two-phase molecular simulation system as described above.

[0014] The above-mentioned technical solution of this application has the following beneficial technical effects: In this embodiment, based on the chemical composition and structure of the promoter, a molecular structure of the promoter carrying a charge distribution can be generated, which is particularly suitable for the molecular construction of complex multi-charge ionization promoters. By constructing an empty gas box of a first predetermined volume and an empty aqueous solution box of a second predetermined volume, a predetermined number of gas molecules are inserted into the empty gas box to obtain a filled gas box. A predetermined number of promoter molecules and water molecules are inserted into the empty aqueous solution box to obtain a filled aqueous solution box. Finally, the filled gas box and the aqueous solution box are spliced ​​together to form a molecular simulation system with a gas-liquid two-phase interface. By keeping the types and quantities of molecules in the filled aqueous solution box constant, the gas storage efficiency of the promoter for different gases can be evaluated by adjusting the types and quantities of gas molecules; or by keeping the types and quantities of gas molecules constant and changing the type and quantity of promoter molecules in the aqueous solution box, the gas storage efficiency of different promoters can be evaluated. The above simulation system can be used to evaluate and analyze the gas storage efficiency of different types of promoters for various gases, has universality, and provides a "realistic" environment for simulating the dissolution of gases and / or hydrate formation in aqueous solutions, which can improve the accuracy and efficiency of simulation results. Attached Figure Description

[0015] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings of the embodiments of this application will be briefly described below.

[0016] Figure 1 This is a schematic diagram of the system architecture of an embodiment of this application.

[0017] Figure 2 This is a structural block diagram of a system for constructing a gas-liquid two-phase molecular simulation system of a hydrate promoter according to an embodiment of this application.

[0018] Figure 3 This is a structural block diagram of the structure generation unit in an embodiment of this application.

[0019] Figure 4 This is a structural block diagram of the partitioning construction unit in an embodiment of this application.

[0020] Figure 5 This is a structural block diagram of another hydrate promoter gas-liquid two-phase molecular simulation system according to an embodiment of this application.

[0021] Figure 6 This is a schematic diagram of the fragment structure and the overall molecular simulation structure of the promoter molecule BSS8 in an embodiment of this application.

[0022] Figure 7 This is a schematic diagram of the initial gas-liquid two-phase molecular simulation system architecture after splicing in an embodiment of this application.

[0023] Figure 8These are schematic diagrams of the chemical structures of BSS accelerator molecules with different chain lengths according to embodiments of this application.

[0024] Figure 9 This is a schematic diagram showing the distribution of the promoter molecule BSS at the gas-liquid interface according to an embodiment of this application.

[0025] Figure 10 This is a schematic diagram of the hardware structure of the electronic device used to implement the embodiments of this application. Detailed Implementation

[0026] The principles and spirit of this application will be described below with reference to several exemplary embodiments. It should be understood that these embodiments are provided to make the principles and spirit of this application clearer and more thorough, enabling those skilled in the art to better understand and implement the principles and spirit of this application. The exemplary embodiments provided herein are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments described herein without inventive effort are within the scope of protection of this application. Figure 1 A schematic diagram of the equipment composition framework of the construction system for the gas-liquid two-phase molecular simulation system of the hydrate promoter according to an embodiment of this application is shown. Figure 1 As shown, the system includes a terminal device 12 and a server 14. The terminal device 12 can include at least one of the following: a smartphone, tablet, laptop, desktop computer, smart TV, various wearable devices, augmented reality (AR) devices, virtual reality (VR) devices, etc. A client can be installed on the terminal device 12. For example, the client can be a dedicated client for performing specific functions (such as an application app), or a client with multiple embedded application applets (with different functions), or a client logged in via a browser. Users can operate on the terminal device 12. For example, a user can open the client installed on the terminal device 12 and input commands through the client, or a user can open the browser installed on the terminal device 12 and input commands through the browser. After receiving the user's input command, the terminal device 12 sends a request message containing the command to the server 14. After receiving the request message, the server 14 performs the corresponding processing and then returns the processing result information to the terminal device 12. The user command is completed through a series of data processing and information interaction.

[0027] In this document, terms such as first, second, and third are used only to distinguish one entity (or operation) from another entity (or operation), and are not intended to require or imply any order or relationship between these entities (or operations).

[0028] Figure 2This diagram illustrates a structural block diagram of a construction system for a gas-liquid two-phase molecular simulation system of a hydrate promoter according to an embodiment of this application. The construction system includes a structure generation unit 100, a partitioned construction unit 200, and a gas-liquid splicing unit 300. The structure generation unit 100 is used to generate an optimized molecular structure of the promoter based on the chemical composition and molecular structure of the promoter to be evaluated; wherein the optimized molecular structure of the promoter carries the charge distribution result. The partitioned construction unit 200 is used to construct an empty gas box with a first set volume and an empty aqueous solution box with a second set volume; a first set number of gas molecules are inserted into the empty gas box to obtain a filled gas box; a second set number of optimized promoter molecules and a third set number of water molecules are inserted into the empty aqueous solution box to obtain a filled aqueous solution box; and the gas-liquid splicing unit 300 is used to splice the filled gas box and the filled aqueous solution box to obtain a gas-liquid two-phase molecular simulation system.

[0029] The molecular simulation system construction system provided in this application relies on a molecular simulation platform 11, which includes, for example, a molecular structure model library, a charge model library, and a force field parameter model library. The molecular structure model library stores the chemical formulas and two-dimensional or three-dimensional molecular structures of various gases and promoters, while the force field parameter model library stores different force field parameter models for various gases, promoters, and water molecules. The molecular structure model library, charge model library, and force field parameter model library can be stored in the database of server 14, and an index can be created in the database to construct a model library for use by users of terminal device 12.

[0030] Gases such as methane, hydrogen, or carbon dioxide, and promoters such as DIOX or THF, can be used. On the molecular simulation platform, the user of terminal device 12 can input the chemical formula, two-dimensional or three-dimensional molecular structure of the promoter to be evaluated, or the chemical formula, two-dimensional or three-dimensional molecular structure can be obtained from the database of server 14. The system determines whether the molecular structure of the promoter to be evaluated is a neutral molecule or a charged group. If the molecular structure is determined to be a charged group, the charge quantity of the promoter is calculated. The structure generation unit 100 can generate promoter molecular structures with accurate charge distributions by optimizing the molecular structure of the promoter, which is particularly suitable for constructing complex molecular structures of multi-charge ionization promoters. This is achieved through quantization. Optimizing the charge distribution of promoters through computation or force field fitting can accurately describe the hydrogen bonding between the promoter and water molecules (such as the positively charged hydrogen atoms of H2O), thus stabilizing the structure of aqueous solutions. Therefore, an accurate charge distribution allows the interaction between the promoter and water molecules to be realistically reproduced in simulations. Furthermore, an accurate charge distribution allows for the accurate calculation of the dispersion forces between gas molecules and the promoter. For example, the Lennard-Jones potential of the dispersion force between gas molecules H2 and the promoter DIOX can be accurately calculated, thereby simulating the solubility and diffusion behavior of gases in aqueous solutions. This allows the promoter molecular structure to be directly used in subsequent gas or aqueous solution box construction, which is more conducive to the analysis of complex multi-charged ionization promoters.

[0031] The partitioned construction unit 200 can construct empty gas boxes of a first predetermined volume and empty aqueous solution boxes of a second predetermined volume in separate regions. A predetermined number of gas molecules are inserted into the empty gas boxes to obtain filled gas boxes. Predetermined numbers of promoter molecules and water molecules are inserted into the empty aqueous solution boxes to obtain filled aqueous solution boxes. The inserted molecular structures can be, for example, space-filling models, to more closely approximate the actual spatial structure of molecules. For example, by keeping the types and quantities of molecules in the filled aqueous solution boxes constant and adjusting the different gas molecules and their predetermined quantities, the gas storage efficiency of the promoter for different gases can be evaluated and analyzed. Alternatively, by keeping the predetermined quantity of a certain gas molecule constant and changing the promoter molecules and their quantities in the aqueous solution boxes, the gas storage efficiency of different promoters can be evaluated and compared. This simulation system is applicable to evaluating and analyzing the gas storage efficiency of different types of promoters and has universality. The gas-liquid splicing unit 300 splices together a filled gas box and a filled aqueous solution box to form a gas-liquid two-phase molecular simulation system with a gas-liquid interface. This provides a "realistic" environment for subsequent simulations of gas dissolution and / or hydrate formation in aqueous solution, thereby improving the accuracy and efficiency of the simulation results.

[0032] The gas-liquid two-phase molecular simulation system constructed in this application can generate trajectory data from molecular dynamics simulations during the simulated nucleation or growth of gas hydrates. For example, the gas-liquid interfacial tension and the number of gas molecules entering the aqueous solution of the gas-liquid two-phase molecular simulation system per unit time can be obtained from the trajectory data of molecular dynamics simulation. Based on the number of gas molecules newly entering the aqueous solution of the simulation system, the concentration of gas molecules in the aqueous solution of the simulation system can be calculated. When the gas-liquid interfacial tension decreases, gas molecules continuously enter the aqueous solution, thereby increasing the gas concentration in the aqueous solution of the gas-liquid two-phase molecular simulation system. Therefore, the simulation calculation results can reflect the influence of amphoteric surfactant molecules with both hydrophilic and hydrophobic groups on the concentration of gas in the aqueous solution, and are of great significance for studying hydrate nucleation or growth and gas storage applications. Furthermore, the number of newly formed hydrate cages, the mass of gas, promoter, and water in the hydrate, and the mass of the gas cages within the hydrate can be obtained from trajectory data generated by molecular dynamics simulations within a set sampling time. The growth rate of the hydrate can be calculated based on the number of newly formed hydrate cages within the set sampling time. The gas storage capacity of the hydrate promoter can be calculated based on the mass of gas, promoter, and water in the newly formed hydrate. Finally, the gas storage efficiency of the hydrate promoter can be calculated based on the hydrate growth rate and gas storage capacity. The gas storage efficiency of the hydrate promoter allows for a comprehensive quantitative evaluation of its performance, enabling comparisons between different types of promoters, improving the reliability of promoter screening, and accelerating the screening process. This can guide the optimization and iteration of promoters in practical production applications, ultimately promoting the commercial application of hydrate gas storage.

[0033] Figure 3This is a schematic diagram of the structural principle of a structure generation unit according to an embodiment of the present application. In this embodiment, the structure generation unit 100 includes a molecule acquisition module 101, a structure drawing module 102, a charge generation module 103, a structure segment splitting module 104, and a structure segment splicing module 105. The process includes: A molecule acquisition module 101 retrieves the chemical composition and molecular structure of the promoter molecule to be evaluated from the database of server 14, or the user of terminal device 12 can input the chemical formula, two-dimensional or three-dimensional molecular structure of the promoter to be evaluated; a structure drawing module 102 draws an initial structural model of the promoter based on the acquired chemical composition and molecular structure of the promoter molecule; a charge generation module 103 determines whether the molecular structure of the promoter to be evaluated is a neutral molecule or a charged group based on the drawn initial structural model; if the molecular structure of the promoter is a charged group, the charge parameters of the charged group are determined; if the number of charges of the charged group exceeds 2, a structure fragment splitting module 104, based on the molecular topology, splits the molecular structure of the promoter into multiple structural fragments according to the charge parameters of the charged groups and the segmentation generation strategy to achieve charge continuity at the boundaries of the structural fragments; and a structure fragment splicing module 105 splices each structural fragment at its endpoints to output the molecular structure of the promoter. Therefore, by splitting the structural fragment module 104, the molecular structure of the promoter is split into multiple structural fragments, which is especially suitable for constructing the molecular structure of complex multi-charge ionization promoters, enhancing the versatility of the molecular simulation system. The splicing structural fragment module 105 connects each structural fragment at its endpoints through covalent bonds, and recombines them into a complete promoter molecular model, thereby verifying its geometric stability and charge balance, laying the foundation for improving the accuracy of the simulation results.

[0034] In some embodiments, the segmentation module 104 includes a charge allocation submodule and a segmentation submodule, wherein the charge allocation submodule is used to allocate the charge when the charge quantity of the charged group is greater than 2; the segmentation submodule is used to segment the molecular structure of the promoter into multiple structural segments according to the charge quantity allocation result, wherein the charge quantity of each structural segment is less than or equal to 2.

[0035] Specifically, the charge model can be stored in the database of server 14. The charge model may include, for example, the RESP model and the AM1-BCC model. The RESP model is suitable for charge fitting after quantum chemical calculations, while the AM1-BCC model is suitable for charge correction using semi-empirical quantum chemical methods. The chemical properties of charged groups include polarity and functional group type. Based on the chemical properties of the charged groups, an appropriate charge model can be selected to calculate and obtain the charge quantity of the charged group. The charge allocation submodule rationally splits multi-charged groups, ensuring that each structural fragment contains complete functional groups or chemical bonds. This not only ensures the chemical rationality of the structural fragments but also makes the charge distribution closer to the actual chemical environment, thereby improving the accuracy of charge distribution and enhancing the reliability of the simulation. For example, for a promoter molecule structure containing a +3 charge, the three split +1 charge structural fragments can more realistically simulate its diffusion behavior in solution, avoiding the formation of "ion pairs" caused by concentrated charges. Furthermore, by setting the charge quantity of each structural segment to ≤2, the computational complexity in the simulation can be reduced. If the complex molecular simulation structure of the multi-charge ionization promoter is not broken down, the computational workload of the electrostatic interaction of the multi-charge structure increases exponentially, the simulation is prone to crashing, and the simulation calculation cannot proceed normally.

[0036] Figure 4 This is a schematic diagram of the structural principle of a partitioning construction unit 200 according to an embodiment of this application. In this embodiment, the partitioning construction unit 200 includes an aqueous solution box design module 201 and a gas box design module 202. The aqueous solution box design module 201 is used to determine the size of the empty aqueous solution box based on the size of the generated hydrate cell and the number of generated hydrate cages. The size of the empty aqueous solution box includes a length extending along a first direction, a width extending along a second direction, and a depth extending along a third direction. The gas box design module 202 is used to determine the size of the empty gas box based on the size of the empty aqueous solution box. The length and width of the empty gas box are equal to the length and width of the empty aqueous solution box.

[0037] Specifically, the first direction is, for example, the x-axis, the second direction is, for example, the y-axis, and the third direction is, for example, the z-axis. The aqueous solution box design module 201 designs an empty aqueous solution box that can accommodate the growth of the hydrate cage-like crystal while maintaining the stability of the simulation system, based on the size of the hydrate cage-like crystal. For example, the volume of a single unit cell can be calculated based on the lattice constant of the target hydrate (such as type SII hydrate); then, the total volume of the crystal is calculated based on the number of hydrate unit cells required for the simulation and the volume of a single unit cell. This precise matching of the hydrate crystal size ensures sufficient space within the aqueous solution box to accommodate crystal growth, avoiding the crystal being "squeezed" and deformed due to an undersized box, which would affect the realism of the simulation results. The gas box design module 202 designs a matching gas box based on the size of the aqueous solution box to form a stable gas-liquid interface. The length and width of the empty gas box are the same as the empty aqueous solution box, for example, both are 30 × 30 Å, ensuring a smooth interface when the two are joined.

[0038] In some embodiments, the partitioning construction unit 200 further includes a first insertion module 203 and a second insertion module 204. The first insertion module 203 is used to insert a second predetermined number of promoter molecules into the empty aqueous solution box, forming gaps between adjacent promoter molecules. The second insertion module 204 is used to insert water molecules into the gaps to obtain a filled aqueous solution box. In this way, by first inserting macromolecular promoter molecules into the empty aqueous solution box and then filling the gaps with water molecules, the space filling can be optimized.

[0039] In some embodiments, the gas-liquid splicing unit 300 includes a gas-liquid splicing module for placing a filled aqueous solution box between two gas boxes. The filled gas boxes and aqueous solution boxes are arranged and spliced ​​sequentially along a third direction, wherein a predetermined gap is reserved between adjacent boxes. After the gas boxes and solution boxes with the same length and width are spliced ​​along the z-direction, a flat gas-liquid interface can be formed, which can simulate the gas dissolution process in the actual gas-liquid system, such as H2 diffusing from the gas phase to the liquid phase and interacting with the promoter. Furthermore, by reserving a predetermined gap between adjacent gas boxes and aqueous solution boxes, such as 0.5 nm, the formed void layer can prevent edge molecules from overlapping. If edge molecules overlap, the simulation is prone to collapse, causing the simulation calculation to fail.

[0040] In some embodiments, the system further includes a molecular quantity determination unit 400, which determines a first predetermined number of gas molecules, a second predetermined number of promoter molecules, and a third predetermined number of water molecules based on simulated temperature, pressure, and promoter concentration, hydrate cell size, and the number of hydrate cages formed. Specifically, the molecular quantity determination unit 400, based on the input simulated temperature, pressure, promoter concentration, hydrate cell size, and number of hydrate cages formed, can output the first predetermined number of gas molecules, the second predetermined number of promoter molecules, and the third predetermined number of water molecules. For example, in the DIOX-H2 hydrate simulation system, the preset sII hydrate is a 2×2×2 unit cell. First, based on the hydrate crystal structure and the number of unit cells, the third set number of water molecules is calculated. An sII hydrate unit cell contains 136 water molecules, and a 2×2×2 unit cell corresponds to 8 unit cells, so the required number of water molecules is 8×136=1088. Next, based on the concentration ratio of the promoter and water and the number of water molecules, the optimized number of promoter molecules can be obtained. For example, when the DIOX concentration is 5.56 mol%, the number of promoter molecules = number of water molecules × (concentration ratio / (1 - concentration ratio)). The required number of DIOX molecules is 192. Finally, based on the initial temperature and pressure of the simulation system, for example at 270 K and 50 °C... Under MPa conditions, the calculated number of H2 molecules was 384. If more molecules are needed for hydrate growth, the number of each type of molecule can be dynamically adjusted by defining a molecular number unit of 400. These operations improve the accuracy, efficiency, and repeatability of the molecular simulation system, and ensure that the obtained gas-liquid two-phase molecular simulation system is consistent with experimental conditions, thus enhancing the reliability of the molecular simulation system.

[0041] In some embodiments, the system further includes a force field parameter matching unit 500, a calculation unit 600, and a force field parameter optimization unit 700. The force field parameter matching unit 500 is used to match corresponding force field parameters to the gas molecules, promoter molecules, and water molecules contained in the gas-liquid two-phase molecular simulation system based on a gas molecule force field model, a promoter molecule force field model, and a water molecule force field model; wherein the force field parameters include collision radius and potential well depth; the calculation unit 600 is used to calculate the diffusion coefficient, solubility, and hydrate melting point of the gas-liquid two-phase molecular simulation system after matching the force field parameters; the force field parameter optimization unit 700 is used to compare the calculated values ​​of diffusion coefficient, solubility, and hydrate melting point with experimental values, and optimize the matched force field parameters based on the comparison results.

[0042] Specifically, gas molecules can be modeled using the Lennard-Jones (LJ) force field model, water molecules using the TIP4P / ice force field model, and promoter molecules using the OPLS-AA force field model. By inputting the molecular structure into the corresponding force field model, the corresponding force field parameters can be output, such as the collision radius of the molecules. It can describe the spatial size of molecules and the depth of potential wells. It can describe the strength of intermolecular interactions and assign force field parameters to each simulated molecular structure in a gas-liquid two-phase molecular simulation system, by matching accurate collision radii. Sum of potential well depth Parameters can accurately reflect the steric hindrance of molecules (e.g., the collision radius of H2). (The smaller the value, the easier it is to diffuse) and the strength of the interaction.

[0043] The diffusion coefficient describes the diffusion ability of gas molecules in aqueous solution (unit: cm² / s), reflecting the kinematic activity of molecules; solubility measures the amount of gas molecules dissolved in aqueous solution (unit: mol / L or wt%), which is related to gas storage capacity; the hydrate melting point is the melting temperature of the hydrate (unit: K), reflecting the thermodynamic stability of the hydrate. These parameters are used to evaluate core indicators reflecting the storage performance of hydrates, such as gas storage capacity and growth rate. The calculated values ​​(e.g., simulated solubility) output by calculation unit 600 are compared with experimental values ​​to calculate the relative error. The force field parameter optimization unit 700 adjusts the force field parameters based on the calculated relative error. Then, calculation unit 600 is rerun until the relative error is less than a preset threshold. By comparing the calculated and experimental values, the force field parameters are iteratively optimized, making the simulation results closer to the real system and improving simulation accuracy. The experimental values ​​are obtained through experimental evaluation methods using equipment such as high-pressure reactors, high-pressure differential scanning calorimeters, and spectrometers.

[0044] The implementation methods and advantages of the embodiments of this application have been described above through multiple examples. The specific processing procedures of the embodiments of this application are described in detail below with reference to specific examples.

[0045] Example 1 The construction system for a gas-liquid two-phase molecular simulation system of a hydrate promoter may include the following steps in the specific processing: S1: Molecular model of the growth promoter Based on the promoter molecule to be evaluated, a promoter molecule model is drawn and optimized in a molecular simulation platform, such as LigParGen. For complex promoter molecules with a charge number greater than 2, structural fragments can be constructed in segments, spliced ​​together, and then the molecule optimized as a whole. Taking the complex BSS8 type promoter (C16H24N2O12S2Na4) as an example, the specific steps may include the following: S11: Obtain the chemical composition and structure of the promoter molecule, for example, input the chemical structure of the promoter (C16H24N2O12S2Na4) into the LigParGen molecular simulation platform.

[0046] S12: Use the LigParGen simulation platform to draw the initial structural model of the promoter molecule and obtain the file Promote.pdb; For example, the drawn BSS8 does not include Na+ ions, so the initial structure of the BSS8 promoter molecule can carry 4 negative charges.

[0047] S13: Charge Distribution and Parameterization Choose the appropriate charge model, where 1.14 The CM1A-LBCC charge model is used to analyze neutral molecules, 1.14 The CM1A charge model is used to analyze charged groups. A segmented generation strategy is employed to break down the promoter molecule structure into structural fragments carrying ≤2 charges, generating separate structural fragment and charge distribution results. For example, BSS8 carries four negative charges, and particle type 1.14 can be selected. The CM1A charge model analyzes charged groups and breaks down molecular structures into structural segments carrying ≤2 charges, such as... Figure 6 As shown, the promoter A with 4 negative charges is split into A1 and A2, generating 2 structural segments and charge distribution results.

[0048] S14: Assemble and optimize the model By using a custom script, the structural fragments obtained in step S13 are spliced ​​together at their endpoints to form a complete accelerator molecular model. Based on quantum mechanical calculations and optimization of the molecular model, the geometric structure and charge distribution of the accelerator molecular model can be made accurate. Based on the optimized molecular simulation structure and charge distribution of the accelerator, the corresponding molecular simulation structure information of the accelerator is saved.

[0049] S2: Constructing a gas-liquid two-phase molecular simulation system may include the following steps: S21: Construct an empty gas box and an empty aqueous solution box.

[0050] For example, an empty gas cell with a size of x,y,z = 5 × 5 × 2 nm³ can be constructed, resulting in the file gas_initial.pdb. Similarly, an empty aqueous solution cell with a size of x,y,z = 5 × 5 × 6 nm³ can be constructed, resulting in the file solution_initial.pdb.

[0051] S22: Insert gas molecules into an empty gas box, and insert promoter molecules and water molecules into an empty aqueous solution box; preferably, insert large promoter molecules first, and then fill the gaps with water molecules to optimize space filling.

[0052] For example, inserting 2000 CH4 gas simulants into an empty gas box results in a filled gas box (gas.pdb). Similarly, inserting 20 BSS8 promoter optimization simulants into an empty aqueous solution box, followed by 4000 water simulants, results in a filled aqueous solution box (solution.pdb).

[0053] S23: Reference Figure 7 The gas and aqueous solution boxes, which were constructed separately, were spliced ​​along the z-axis using a custom script. After splicing, the initial gas-liquid two-phase molecular simulation system system.pdb was obtained. A 0.5nm gap layer was reserved between different boxes to prevent edge molecules from overlapping.

[0054] S3: Simulation Force Field Parameter Setting and Optimization Based on the molecular categories in the initial gas-liquid two-phase molecular simulation system, corresponding force field parameter models are selected. For water molecules, the Tip4p / Ice force field model is used; for CH4, the OPLS-UA force field model is used; and for H2 and CO2, the TraPPE force field model is used. For promoter molecules, due to their diverse types and complex structures, there are no readily available force field parameters. Force field parameters can be generated based on the OPLS-AA force field model, and these generated parameters are used on the LigParGen molecular simulation platform to improve accuracy.

[0055] Furthermore, for promoter molecules, parameters can be further optimized using first-principles calculations, such as combining first-principles calculations (DFT methods, e.g., B3LYP / 6-31G). On the one hand, the charge distribution of different molecules can be parameterized. On the other hand, the diffusion coefficient, solubility and hydrate melting point calculated based on the gas-liquid two-phase molecular simulation system can be compared with the experimental values, and the force field parameters can be continuously optimized based on the comparison results.

[0056] The above steps enable the construction of a complex BSS8 molecular simulation model and the establishment of the entire BSS8-methane solution simulation system. It allows for the calculation of the diffusion coefficient, solubility, and hydrate melting point of the gas-liquid two-phase molecular simulation system after matching force field parameters. Furthermore, it lays the foundation for subsequent calculations of hydrate promoter growth rate and gas storage capacity within a multi-parameter range (temperature, pressure, and concentration).

[0057] Example 2 The similarities between Example 2 and Example 1 will not be repeated here. The differences are as follows: Figure 8 These are schematic diagrams of the chemical structures of BSS accelerator molecules with different chain lengths. (Reference) Figure 8 For example, the five molecular structures of BSS-2, BSS-4, BSS-8, BSS-12 and BSS-16 are complex molecules containing four negative charges, and the difference between the molecules is that the middle carbon chain gradually increases in length.

[0058] The promoter molecular structure can be generated according to the steps described in Example 1, and a gas-liquid two-phase molecular simulation system with H2O:CH4:BSS = 4000:1000:8 can be constructed. The force field parameters are optimized, and the constructed gas-liquid two-phase molecular simulation system is adjusted to the initial simulation system conditions. A formal simulation of this gas-liquid two-phase molecular simulation system is performed under test conditions of 300K temperature and 10MPa pressure, which can simulate the dissolution process of methane gas in BSS aqueous solution. The simulation calculation results are as follows: Table 1. Methane concentration and gas-liquid interfacial tension in aqueous solutions of BSS simulation systems with different chain lengths.

[0059] To prevent random errors in the simulation results, test parameters can be submitted repeatedly to repeat the simulation under the same test conditions. The average of the simulation results can be taken. The error in Table 1 is the standard deviation of the simulation results from three repeated submissions of test parameters. The simulation results in Table 1 show that as the BSS molecular chain length increases in the gas-liquid two-phase molecular simulation system, the concentration of methane gas in the aqueous solution continuously increases, while the interfacial tension between the gas and liquid in the system continuously decreases. Considering the physicochemical properties of the BSS molecule itself—hydrophilic sulfonic acid, carboxyl, and amide groups on both sides, and a hydrophobic alkane group in the middle carbon chain—increasing carbon chain length leads to increased hydrophobicity of BSS, resulting in more adsorption at the gas-liquid interface. This disrupts the ordered distribution of gas-liquid molecules at the interface, leading to a decrease in interfacial tension. Consequently, methane molecules continuously enter the aqueous solution, increasing the methane concentration in the aqueous solution of the gas-liquid two-phase molecular simulation system. The simulation results above accurately reflect the effect of amphoteric surfactant molecules with both hydrophilic and hydrophobic groups on the concentration of gas in aqueous solution, and are of great significance for studying hydrate nucleation or growth and gas storage applications.

[0060] Trajectory data for molecular dynamics simulations can be generated during the simulation of gas hydrate nucleation or growth; Reference Figure 9 At the gas-liquid interface shown by the dashed circle, the hydrophobic carbon chain groups of BSS (the white molecular structures shown in the figure are hydrophobic carbon chain groups) are embedded in the gas, while the hydrophilic groups on both sides (the red molecular structures shown in the figure are hydrophilic groups) are adsorbed in the aqueous solution. The trajectory data generated by the molecular dynamics simulation is consistent with the conclusion found through experiments that the sulfonic acid groups, carboxyl groups, and amide groups on both sides are hydrophilic groups, and the alkyl group in the middle is a hydrophobic group. This verifies that the gas-liquid two-phase molecular simulation system constructed in this application and the simulation calculation results are accurate.

[0061] The system for constructing a gas-liquid two-phase molecular simulation system for hydrate promoters provided in this application expands the universality of molecular structure models. It is particularly applicable to constructing gas-liquid two-phase molecular simulation systems for complex promoters, including bio-based polymers or ionic surfactants. The simulation results can be used to analyze the effect of promoter molecules on the concentration of gas in aqueous solution, so as to determine whether the promoter promotes or inhibits the dissolution of gas in aqueous solution. This is of great significance for studying hydrate nucleation or growth and gas storage applications, and can extend the applicability of simulation calculations.

[0062] This application also provides a method for calculating the gas storage efficiency of a hydrate promoter. Based on the gas-liquid two-phase molecular simulation system constructed in the above embodiments, the method includes the following steps: S110: Input different sets of test parameters into the constructed gas-liquid two-phase molecular simulation system to form parameter control under a multivariable grid simulation framework, so as to realize the simulation of gas hydrate nucleation or growth.

[0063] Specifically, for example, the test parameter set may include multiple variables such as temperature, pressure, and promoter concentration. By using a grid design within the set temperature range, pressure range, and promoter concentration range, and combining the parameter values ​​of multiple variables, different test parameter sets can be obtained, thereby covering the parameter control of multiple variables. In the process of simulating the nucleation or growth of gas hydrates, the variable factors that dominate the changes in the gas storage efficiency of the promoter can be identified, thereby reducing the blindness of the experiment.

[0064] S120: Generate trajectory data for molecular dynamics simulation during the simulated nucleation or growth of gas hydrates; the trajectory data for molecular dynamics simulation includes: the number of newly formed hydrate cages within a set sampling time, as well as the mass of gas, the mass of promoter, and the mass of water in the hydrate.

[0065] S130: Based on trajectory data from molecular dynamics simulations and a pre-constructed mathematical model of gas storage efficiency, the gas storage efficiency of the hydrate promoter is obtained.

[0066] Specifically, through trajectory analysis of molecular dynamics simulations, the number of newly formed hydrate cages within a set sampling time, as well as data such as the mass of gas, promoter, and water trapped in the hydrate, can be obtained. Based on the trajectory data from the molecular dynamics simulations, the growth rate and gas storage capacity of the hydrate promoter can be calculated. For example, the growth rate of the hydrate promoter can be calculated based on the number of newly formed hydrate cages within a set sampling time, and the accurate result of the gas storage capacity of the hydrate promoter can be obtained based on the mass of gas, promoter, and water in the hydrate. The pre-constructed mathematical model for gas storage efficiency integrates the two evaluation indicators of the hydrate promoter's growth rate and gas storage capacity, and assigns flexible weighting factors, which can be adjusted according to thermodynamics. The economic efficiency of the conditions, as well as the impact of growth rate and gas storage capacity on economic effectiveness, are prioritized and weighted. Therefore, the corresponding trajectory data are substituted into the pre-constructed mathematical model of gas storage efficiency for calculation, which yields the gas storage efficiency of the hydrate promoter. This allows for a comprehensive quantitative evaluation of the promoter's performance. Compared to experimental methods, it saves experimental costs. Moreover, the simulation calculation method in this application is repeatable, which can accurately calculate the gas storage efficiency of the hydrate promoter under different conditions. This facilitates multi-dimensional comparison of hydrate promoters, improves the reliability of promoter screening, and accelerates the screening process of different promoters based on the gas storage efficiency of the hydrate promoter. This can guide the optimization and iteration of promoters in actual production applications, and promote the commercial application of hydrate gas storage.

[0067] In some embodiments, step S130, which involves obtaining the gas storage efficiency of the hydrate promoter based on trajectory data from molecular dynamics simulations and a pre-constructed mathematical model of gas storage efficiency, includes the following specific steps: S131: The growth rate of the hydrate promoter is calculated based on the number of newly formed hydrate cages within the set sampling time. S132: The gas storage capacity of the hydrate promoter is calculated based on the mass of gas in the hydrate, the mass of the promoter, and the mass of water. S133: The gas storage efficiency of the hydrate promoter is calculated based on the growth rate and gas storage capacity of the hydrate promoter, as well as the growth rate and gas storage capacity of pure gas hydrate without promoter.

[0068] Specifically, the growth rate R of the hydrate promoter can be calculated according to the following conditional formula:

[0069] In the formula, To set the sampling time The number of newly formed hydrate cages, and the structure of the hydrate cages, for example, can be 5. 12 , 5 12 6 2 , 5 12 6 4 The growth rate of any of the hydrate promoters is calculated to be consistent.

[0070] The gas storage capacity Q of the hydrate promoter can be calculated according to the following conditional formula:

[0071] In the formula, To capture the mass of gas in the hydrate, and These are the mass of the accelerator and the mass of the water, respectively.

[0072] In some embodiments, the gas storage efficiency of the hydrate promoter is calculated according to the following conditional formula:

[0073] In the formula, E represents the gas storage efficiency of the hydrate promoter, R and Q represent the growth rate and gas storage capacity of the promoter-induced hydrate, respectively, and R0 and Q0 represent the growth rate and gas storage capacity of the pure gas hydrate without the promoter, respectively. and These are the corresponding factor weight parameters. Among them, the weights can be flexibly adjusted based on the economic efficiency of thermodynamic conditions, as well as the magnitude of the impact of growth rate and gas storage capacity on economic effectiveness. and Weight, if set =0.3, =0.7, meaning that the gas storage capacity factor is more important for evaluating the gas storage efficiency of hydrate promoters.

[0074] In some embodiments, the method further includes the following specific steps: S101: Perform energy minimization processing on the gas-liquid two-phase molecular simulation system, and use the steepest descent algorithm to eliminate high-energy conflicts in the initial molecular simulation structure of the gas-liquid two-phase molecular simulation system. Terminate the optimization process when the maximum interaction force between molecules in the gas-liquid two-phase molecular simulation system is less than the preset convergence threshold. S102: The temperature-pressure coupling algorithm is used to perform pre-equilibrium simulation calculations on the gas-liquid two-phase molecular simulation system after energy minimization, so that the temperature and pressure of the gas-liquid two-phase molecular simulation system reach the initial conditions of the target simulation.

[0075] Specifically, energy minimization can be performed on the gas-liquid two-phase molecular simulation system. The steepest descent method can be used to eliminate high-energy conflicts in the initial stage. The optimization process is terminated when the maximum interaction force between molecules in the gas-liquid two-phase molecular simulation system is less than a preset convergence threshold, such as 1000 KJ / mol / nm. This eliminates undesirable contacts and unreasonable geometric structures in the gas-liquid two-phase molecular simulation system, such as undesirable contacts that may occur when there are three-dimensional conflicts between atoms, so that the gas-liquid two-phase molecular simulation system is in a local minimum energy state. Before the formal simulation calculation, a pre-equilibrium simulation calculation is performed on the gas-liquid two-phase molecular simulation system that has undergone energy minimization treatment, using a temperature-pressure coupling algorithm, such as the Berendsen thermostat temperature-pressure coupling algorithm. This algorithm has fast convergence and high computational efficiency, which can enable the gas-liquid two-phase molecular simulation system to quickly reach the target temperature in the initial stage. The time step of the pre-equilibrium simulation calculation can be set to 1 femtosecond to ensure the accuracy of the calculation. After setting parameters such as temperature, pressure, promoter concentration and time step, a pre-equilibrium simulation calculation of at least 2 nanoseconds is performed on the gas-liquid two-phase molecular simulation system to allow the temperature and pressure of the gas-liquid two-phase molecular simulation system to gradually transition to the initial conditions that meet the formal simulation.

[0076] In some embodiments, the test parameter set includes temperature, pressure, and promoter concentration. Step S110: Inputting different sets of multiple test parameters into the constructed gas-liquid two-phase molecular simulation system to form parameter control under a multivariable grid simulation framework to achieve simulated gas hydrate nucleation or growth includes the following specific steps: S111: Set the temperature range, pressure range, and accelerator concentration range, and set the corresponding step size for the set temperature range, pressure range, and accelerator concentration range, as well as set the corresponding test reference conditions. S112: Under the corresponding test reference conditions, the set temperature range, pressure range and accelerator concentration range are combined according to the corresponding step size to obtain the multiple test parameter groups; S113: Submit the multiple test parameter groups according to the set time step, and perform the target simulation calculation task on the gas-liquid two-phase molecular simulation system after the pre-equilibrium simulation calculation is completed; S114: Submit the multiple test parameter sets repeatedly to perform the target simulation calculation task on the gas-liquid two-phase molecular simulation system, in order to eliminate random errors in the calculation results of the target simulation; wherein, The computational task of the target simulation includes performing gas hydrate nucleation or growth simulation in the gas-liquid two-phase molecular simulation system under the temperature, pressure and promoter concentration conditions corresponding to the multiple test parameter groups, and generating trajectory data for molecular dynamics simulation.

[0077] Specifically, for example, the temperature range can be set to 230-300 K with a corresponding step size of 10 K; the pressure range to 0.1-50 MPa with a corresponding step size of 5 MPa; and the promoter concentration range to 0.1-10 mol% with a corresponding step size of 2 mol%. The baseline conditions can be parameter values ​​near the phase equilibrium curve or determined based on previous experimental / simulation results. Orthogonally combining temperature, pressure, and promoter concentration according to the set step sizes generates multiple test parameter sets. A full factorial design can be used to cover all parameter combinations, and scanning the test parameter sets with the baseline conditions as the center allows for rapid identification of the sensitivity of parameters to simulation results. Through the full factorial design approach, the influence of each parameter on hydrate nucleation / growth can be systematically analyzed, such as whether increased temperature inhibits hydrate nucleation or whether increased promoter concentration accelerates hydrate growth, avoiding the limitations of single-factor experiments. Simulation tasks can be submitted in batches according to test parameter sets using script tools, leveraging parallel computing resources to shorten simulation time. Initial conditions in molecular dynamics simulations (such as molecular position and velocity) can affect the simulation results. These results can include trajectory data from the molecular dynamics simulation, such as hydrate nucleation time, gas mass in the hydrate, mass of the promoter, and mass of water. Repeatedly submitting test parameter sets can eliminate random errors and improve the reliability of the simulation results. If the simulation results differ significantly after repeatedly submitting test parameter sets, it indicates instability in the gas-liquid two-phase molecular simulation system. In such cases, simulation conditions can be adjusted, such as extending the pre-equilibrium simulation time or optimizing the force field parameters.

[0078] Figure 10This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of this application. The electronic device can be implemented as a server or other various terminal devices, such as desktop personal computers, tablet computers, laptop computers, mobile phones, etc., including a processor 601 and a memory 602. The memory 602 stores a program instruction set. When the processor 601 executes the program instruction set in the memory 602, the system for constructing the hydrate promoter gas-liquid two-phase molecular simulation system described in this application is realized.

[0079] Specifically, the processor 601 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0080] Memory 602 may include mass storage for data or instructions. For example, and not limitingly, memory 602 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 602 may include removable or non-removable (or fixed) media. Where appropriate, memory 602 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, memory 602 is non-volatile solid-state memory.

[0081] The memory may include read-only memory (ROM), random access memory (RAM), disk storage media devices, optical storage media devices, flash memory devices, and electrical, optical, or other physical / tangible memory storage devices. Therefore, typically, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it can implement the construction system for the hydrate promoter gas-liquid two-phase molecular simulation system described in this application.

[0082] In one example, the electronic device may also include a communication interface 603 and a bus 610. The processor 601, memory 602, and communication interface 603 are connected via the bus 610 and communicate with each other.

[0083] The communication interface 603 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0084] Bus 610 includes hardware, software, or both, that couples components of an online data traffic metering device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 610 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, any suitable bus or interconnect is contemplated herein.

[0085] This application also provides a computer-readable storage medium storing computer program instructions thereon, which, when executed by a processor, implement the construction system of any of the hydrate promoter gas-liquid two-phase molecular simulation systems in the foregoing embodiments. The computer-readable storage medium can be any tangible medium that contains or stores computer-executable instructions for use by or in connection with an instruction execution system, apparatus, or device. The storage medium can be a transient computer-readable storage medium or a non-transitory computer-readable storage medium. Non-transitory computer-readable storage media include, but are not limited to, magnetic storage devices, optical storage devices, and / or semiconductor storage devices. Examples of such storage devices include magnetic disks, optical discs based on CD, DVD, or Blu-ray technology, and persistent solid-state storage such as flash memory and solid-state drives.

[0086] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and illustrated as examples.

[0087] It should be noted that this application is not limited to the specific configurations and processes described above or shown in the figures. The above descriptions are merely specific embodiments of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the described systems, devices, modules, or units can be referred to the corresponding processes in the method embodiments, and need not be repeated here. It should be understood that the scope of protection of this application is not limited thereto. Any person skilled in the art can conceive of various equivalent modifications or substitutions within the scope of the technology disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application.

Claims

1. A system for constructing a gas-liquid two-phase molecular simulation system for hydrate promoters, characterized in that, include: A structure generation unit is used to generate an optimized molecular structure of the accelerator based on the chemical composition and molecular structure of the accelerator to be evaluated, the optimized molecular structure of the accelerator carrying charge distribution results. The partitioned construction unit is used to construct an empty gas box with a first set volume and an empty aqueous solution box with a second set volume, and to insert a first set number of gas molecules into the empty gas box to obtain a filled gas box, and to insert a second set number of optimized accelerator molecules and a third set number of water molecules into the empty aqueous solution box to obtain a filled aqueous solution box. The gas-liquid splicing unit is used to splice the filled gas box and the aqueous solution box to obtain a gas-liquid two-phase molecular simulation system.

2. The system according to claim 1, characterized in that, The structure generation unit includes: The molecular acquisition module is used to acquire the chemical composition and molecular structure of the promoter molecule to be evaluated; The structure drawing module is used to draw an initial structural model based on the chemical composition and molecular structure of the accelerator molecule to be evaluated. The charge generation module is used to generate the charge parameters of charged groups based on the drawn initial structural model; The segmentation module is used to split the molecular structure of the promoter into multiple structural segments based on the charge parameters of the charged groups and the segmentation generation strategy. The structural fragment splicing module is used to splice each structural fragment at its endpoints to obtain the optimized molecular structure of the promoter.

3. The system according to claim 2, characterized in that, The split structure fragment module includes: The charge allocation submodule is used to allocate the charge when the number of charges of a charged group is greater than 2. The structure splitting submodule is used to split the molecular structure of the promoter into multiple structural fragments based on the distribution of charge, wherein the charge of each structural fragment is less than or equal to 2.

4. The system according to claim 1, characterized in that, The partitioning construction unit includes: An aqueous solution box design module is used to determine the size of the empty aqueous solution box based on the size of the generated hydrate cell and the number of generated hydrate cages; wherein the size of the empty aqueous solution box includes the length extending along a first direction, the width extending along a second direction, and the depth extending along a third direction. A gas box design module is used to determine the dimensions of an empty gas box based on the dimensions of an empty aqueous solution box; wherein the length and width of the empty gas box are equal to the length and width of the empty aqueous solution box.

5. The system according to claim 4, characterized in that, The partitioning construction unit also includes: The first insertion module is used to insert a second predetermined number of optimized molecules of accelerator into an empty aqueous solution box, with gaps formed between adjacent optimized accelerator molecules; The second insertion module is used to insert water molecules into the gaps to obtain a filled aqueous solution box.

6. The system according to claim 4, characterized in that, The gas-liquid splicing unit includes: The gas-liquid splicing module is used to place a filled aqueous solution box between two gas boxes. The filled gas boxes and aqueous solution boxes are arranged and spliced ​​sequentially along a third direction, with a predetermined gap reserved between adjacent boxes.

7. The system according to claim 1, characterized in that, Also includes: A molecular quantity unit is defined, which is used to determine a first set number of gas molecules, a second set number of optimized promoter molecules, and a third set number of water molecules based on simulated temperature, pressure, and promoter concentration, the size of the hydrate cell, and the number of hydrate cages generated.

8. The system according to any one of claims 1-7, characterized in that, Also includes: The force field parameter matching unit is used to match the corresponding force field parameters for the gas molecules, promoter molecules, and water molecules contained in the gas-liquid two-phase molecular simulation system based on the gas molecule force field model, the promoter molecule force field model, and the water molecule force field model; wherein, the force field parameters include the collision radius and the potential well depth; The simulation unit is used to calculate the diffusion coefficient, solubility, and hydrate melting point of the gas-liquid two-phase molecular simulation system after matching the force field parameters. The optimized force field parameter unit is used to compare the calculated values ​​of diffusion coefficient, solubility, and hydrate melting point with experimental values, and optimize the matched force field parameters based on the comparison results.

9. An electronic device comprising a processor and a memory, wherein the memory stores a set of computer program instructions, characterized in that, The system for constructing the gas-liquid two-phase molecular simulation system of the hydrate promoter as described in any one of claims 1-8 is implemented when the processor executes the computer program instruction set in the memory.

10. A computer-readable storage medium, wherein, The computer-readable storage medium stores a set of computer program instructions, characterized in that, when the set of computer program instructions is executed by a processor, it implements the construction system of the hydrate promoter gas-liquid two-phase molecular simulation system according to any one of claims 1-8.

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