A method for predicting gas liquefaction temperature

Abstract

This invention discloses a method for predicting the liquefaction temperature of a gas, comprising: obtaining an initial gas crystal structure; obtaining a stable molecular mechanical environment gas crystal structure based on density functional theory; obtaining a stable force field energy environment gas crystal structure using Compass II force field optimization; calculating the average interaction force and density of each single molecule in the two gas crystal structures respectively; comparing the average interaction force and density of the two gas crystal structures to obtain an initial liquefaction temperature prediction model; continuously adjusting the force field parameters of the initial gas crystal structure in the initial liquefaction temperature prediction model to update the initial liquefaction temperature prediction model to obtain the best-fitting liquefaction temperature prediction model; and incorporating the amorphous unit cells of multiple gas molecules to be tested into the best liquefaction temperature prediction model to obtain liquefaction temperature curves and determine the liquefaction temperature range. The gas liquefaction temperature prediction method disclosed in this invention can accurately predict the liquefaction temperature of a gas.

Description

Technical Field

[0001] This invention relates to the field of insulating medium technology, specifically to a method for predicting the liquefaction temperature of a gas. Background Technology

[0002] Gas-based insulating materials are gases that maintain insulation between electrodes with potential differences. They must possess self-recovery capabilities after damage and exhibit characteristics such as minimal dielectric loss, non-flammability, non-explosiveness, and non-aging. In recent decades, sulfur hexafluoride (SF6) gas has been widely used as an insulating gas in various high-voltage electrical equipment due to its high dielectric strength, good arc-quenching ability, and good chemical stability. However, SF6 has a global warming potential (GWP) as high as 24,300, and its decomposition in the atmosphere takes more than 3,200 years. Therefore, finding a new generation of environmentally friendly gaseous insulating media to replace SF6 can not only fundamentally solve the power industry's dependence on SF6 but also align with the concept of green and low-carbon development.

[0003] Since insulating gases must be gaseous at room temperature, liquefaction temperature is a crucial performance indicator for all types of insulating gases, regardless of their form, when searching for environmentally friendly gaseous insulating media to replace SF6. Experimentally measuring the liquefaction temperature of all candidate insulating gas molecules is clearly impractical. First, obtaining the liquefaction temperature of insulating gases experimentally is often costly. Second, the liquefaction temperature of the insulating gas molecules to be synthesized cannot be obtained experimentally. Third, experiments on the liquefaction temperatures of different gas mixtures are cumbersome and complex, making complete determination extremely difficult. Therefore, there is an urgent need to find a method to predict the liquefaction temperature of insulating gas molecules.

[0004] In the prior art, patent publication number CN110793888A discloses an experimental method for the diffusion characteristics of SF6 / N2 mixed gas. This method simulates the molecular motion of mixed gases with different proportions and two pure components under different temperatures and pressures. Statistical analysis of the trajectories yields information such as gas condensation and molecular diffusion coefficients. Based on this information, it provides qualitative and quantitative insights for selecting the proportions of the mixed gas and for gas replenishment and maintenance, which is beneficial for studying the morphology and diffusion of mixed gases with different proportions. However, the diffusion characteristics of the mixed gas in the prior art do not involve a phase transition. Summary of the Invention

[0005] The technical problems to be solved by this invention are as follows: First, obtaining the liquefaction temperature of insulating gases through experimental methods is often costly. Second, the liquefaction temperature of insulating gas molecules to be synthesized cannot be obtained experimentally. Third, obtaining the liquefaction temperature of different mixed gas configurations is cumbersome and complex, making it difficult to obtain completely.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0007] A method for predicting the liquefaction temperature of a gas includes the following steps:

[0008] S100, establish an amorphous unit cell for multiple gas molecules to obtain the initial gas crystal structure;

[0009] S200, based on density functional theory, optimizes the bonding parameters and unit cell parameters of the initial gas crystal structure to obtain a stable molecular mechanical environment gas crystal structure;

[0010] S300, using the Compass II force field, performs energy initialization on the initial gas crystal structure to obtain a stable force field energy environment gas crystal structure;

[0011] S400, calculate the average interaction force and density of each single molecule in the molecular mechanical environment gas crystal structure and the force field energy environment gas crystal structure, respectively;

[0012] S500, compare the average interaction forces and densities of the molecular mechanical environment gas crystal structure and the force field energy environment gas crystal structure respectively to obtain the initial liquefaction temperature prediction model;

[0013] S600, continuously adjust the force field parameters of the Compass II force field of the initial gas crystal structure in the initial liquefaction temperature prediction model, update the initial liquefaction temperature prediction model, and obtain the best-fitting liquefaction temperature prediction model.

[0014] S700, the amorphous unit cells of multiple gas molecules to be tested are introduced into the optimal liquefaction temperature prediction model to perform heating and cooling simulations, obtain the liquefaction temperature curve, and obtain the liquefaction temperature range based on the liquefaction temperature curve.

[0015] Advantages: This method is the first to propose a method for fitting molecular force fields by comparing molecular structure and energy data. The fitting parameters include bonding and non-bonding parameters, and the complete force field parameters obtained can be used to predict liquefaction temperatures. It is also the first to use the force field parameters fitted to individual molecules to calculate the liquefaction temperature of mixed gases, and it is low-cost, solving the problem that the liquefaction temperatures of syngas and mixed gases are difficult to achieve experimentally.

[0016] In one embodiment of the present invention, the average interaction force is obtained by the following formula:

[0017]

[0018] In the formula, E0 is the average interaction force, E total E is the total energy of the gas crystal. moLet n be the energy of a single molecule, and n be the number of molecules.

[0019] In one embodiment of the present invention, obtaining the optimal liquefaction temperature prediction model includes: updating the initial liquefaction temperature prediction model once for each adjustment of the force field parameters of the initial gas crystal structure, and performing an energy initialization on the initial gas crystal structure once for each update, and calculating the corresponding average interaction force and density, until the average interaction force and density are close to the average interaction force and density of the gas crystal structure of the molecular mechanical environment, and then taking the fitted liquefaction temperature prediction model at this time as the optimal liquefaction temperature prediction model.

[0020] In one embodiment of the present invention, the similar judgment criterion is: the average interaction force and density calculated by the updated gas crystal structure have an error of less than 2% compared with the average interaction force and density of the molecular mechanical environment gas crystal structure.

[0021] In one embodiment of the present invention, the following steps are included when performing a temperature rise simulation:

[0022] S711, initialize the energy of the optimal liquefaction temperature prediction model, and bring the amorphous unit cells of multiple gas molecules to be tested into the optimal liquefaction temperature prediction model after energy initialization.

[0023] S712, under a canonical ensemble, sets the initial temperature and heating step size to construct a dynamic simulation environment;

[0024] S713, at the initial temperature, for each heating step increase, a molecular dynamics simulation is performed on the environment where the optimal liquefaction temperature prediction model is located, and the stable structure at this temperature is obtained, and the density of the environment where the optimal liquefaction temperature prediction model is located at this temperature is recorded.

[0025] S714, Repeat step S713 until the liquid system of the gas molecules to be tested boils and completely vaporizes, determine the density mutation point during the gradual heating process, and record the first mutation temperature at this time.

[0026] In one embodiment of the present invention, the cooling simulation includes the following steps:

[0027] S721, set the cooling step size, and gradually cool down after the gas molecules to be measured are completely vaporized;

[0028] S722: For each cooling step decrease, a molecular dynamics simulation is performed on the environment of the optimal liquefaction temperature prediction model, and the stable structure at this temperature is obtained. The density of the environment of the optimal liquefaction temperature prediction model at this temperature is also recorded.

[0029] S723, repeat step S722 until the gaseous system of the gas molecules to be tested is completely liquefied, determine the density abrupt change point during the gradual cooling process, and record the second abrupt change temperature at this time.

[0030] In one embodiment of the present invention, a liquefaction temperature curve is plotted using density data obtained during heating simulation and density data obtained during cooling simulation; in the liquefaction temperature curve, the range between the first abrupt change temperature and the second abrupt change temperature is the liquefaction temperature range.

[0031] In one embodiment of the present invention, the cooling step size is equal to the heating step size.

[0032] In one embodiment of the present invention, the first mutation temperature and the second mutation temperature are phase transition temperatures.

[0033] In one embodiment of the present invention, the heating simulation and the cooling simulation are not in any particular order.

[0034] Compared with the prior art, the beneficial effects of the present invention are: it can accurately predict the liquefaction temperature of the gas, and the process is simple. It has the advantages of stable cost, ease of implementation, and high calculation efficiency, and can provide a useful reference for finding insulating gases. Attached Figure Description

[0035] Figure 1 This is a flowchart of a gas liquefaction temperature prediction method according to an embodiment of the present invention.

[0036] Figure 2 This is a schematic diagram of the C4F7N crystal structure according to an embodiment of the present invention.

[0037] Figure 3 This is the liquefaction temperature curve of Example 1 of the present invention.

[0038] Figure 4 This is the liquefaction temperature curve of Example 2 of the present invention.

[0039] Figure 5 This is a schematic diagram of the crystal structure of water according to an embodiment of the present invention.

[0040] Figure 6 This is the liquefaction temperature curve of Example 3 of the present invention. Detailed Implementation

[0041] To facilitate understanding of the technical solution of the present invention by those skilled in the art, the technical solution of the present invention will now be further described in conjunction with the accompanying drawings.

[0042] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0043] Please see Figure 1 As shown, the present invention provides a method for predicting the liquefaction temperature of a gas, comprising the following steps:

[0044] S100, establish an amorphous unit cell for multiple gas molecules to obtain the initial gas crystal structure.

[0045] Please see Figure 2 As shown, in this embodiment, C4F7N is used as an example. In the Amorphous Cell, the ambient temperature is set to 268K and the density is set to 1.5 g / cm³. 3 The initial environment for constructing the initial gas crystal structure is obtained, and then 100 amorphous unit cells of C4F7N molecules are built in the initial environment to obtain the initial C4F7N crystal structure.

[0046] S200, based on density functional theory, optimizes the bonding parameters and unit cell parameters of the initial gas crystal structure to obtain a stable molecular mechanical environment gas crystal structure.

[0047] S300 uses the Compass II force field to initialize the energy of the initial gas crystal structure, thereby obtaining a stable force field energy environment gas crystal structure.

[0048] In this embodiment, since the Compass II force field is a high-precision force field capable of performing atomic-scale simulation studies on the system, the Compass II force field is selected to initialize the energy of the initial C4F7N crystal structure, that is, to perform initial operation on the disordered crystal structure, so that the energy is reduced and vibrates within a reasonable range, thus obtaining a reasonable structure that can be used for molecular dynamics simulation.

[0049] S400, calculate the average interaction force and density of each single molecule in the molecular mechanical environment gas crystal structure and the force field energy environment gas crystal structure, respectively.

[0050] Specifically, the average interaction force is obtained using the following formula:

[0051]

[0052] In the formula, E0 is the average interaction force, E total E is the total energy of the gas crystal. moLet n be the energy of a single molecule, and n be the number of molecules.

[0053] The density can be obtained using the following formula:

[0054] ρ=m / V;

[0055] In the formula, ρ is the density of the crystal structure, m is the mass of the crystal in the crystal structure, and V is the volume of the crystal structure.

[0056] Boiling of a gas is the process of the disappearance of intermolecular forces, while liquefaction is the regeneration of intermolecular forces. Therefore, liquefaction temperature is closely related to intermolecular forces. These intermolecular forces depend on the molecular structure, with different structures resulting in different molecular masses. Furthermore, the volume difference determined by intermolecular distance and density are also crucial evaluation parameters. Therefore, it is necessary to obtain the average interaction force of each single molecule in the crystal structure and the density of the crystal structure.

[0057] S500, compare the average interaction forces and densities of the molecular mechanical environment gas crystal structure and the force field energy environment gas crystal structure respectively to obtain an initial liquefaction temperature prediction model.

[0058] In this embodiment, the average interaction force E1 and density ρ1 of the gas crystal structure in the molecular mechanical environment are obtained through the average interaction force and density formula, and the average interaction force E2 and density ρ2 of the gas crystal structure in the force field energy environment are obtained. The average interaction force and density of the two are subtracted respectively to obtain the initial liquefaction temperature prediction model.

[0059] S600, continuously adjust the force field parameters of the Compass II force field of the initial gas crystal structure in the initial liquefaction temperature prediction model, update the initial liquefaction temperature prediction model, and obtain the best-fitting liquefaction temperature prediction model.

[0060] In this embodiment, obtaining the optimal liquefaction temperature prediction model includes: updating the initial liquefaction temperature prediction model once for each adjustment of the force field parameters of the initial gas crystal structure, and performing an energy initialization on the initial gas crystal structure once for each update, and calculating the corresponding average interaction force and density, until the average interaction force and density are close to the average interaction force and density of the gas crystal structure in the molecular mechanical environment, and then using the fitted liquefaction temperature prediction model at this time as the optimal liquefaction temperature prediction model.

[0061] Specifically, the similarity criterion is that the average interaction force and density calculated from the updated gas crystal structure have an error of less than 2% compared with the average interaction force and density of the gas crystal structure in the molecular mechanical environment.

[0062] The force field parameters of the Compass II force field in this step include bonding parameters and non-bonding parameters. The bonding parameters include bond length, bond angle, and dihedral angle, while the non-bonding parameters include molecular charge and van der Waals force.

[0063] Molecular dynamics, based on Newton's laws of motion, effectively records the trajectories of molecules within a system. The accuracy of the molecular force field energy directly determines the success or failure of computational simulations; therefore, obtaining highly accurate force field parameters is crucial for simulation. For a chemical reaction, if a suitable force field can be fitted, the actual reaction can be simulated under specific temperature and pressure conditions. The molecular force field is a set of parameterized empirical potential functions describing the interactions between atoms in a system. It mainly consists of two parts: bonding parameters describing intramolecular bonding interactions and non-bonding parameters describing intermolecular interactions, which describe the interactions between unbonded atoms or groups. Based on these parameters, a new force field can be constructed for a specific system like an insulating gas. Using molecular dynamics methods, the gradual cooling process of the gas can be simulated to observe the distances, densities, and forces between molecules, thereby obtaining the relationship between temperature and density, and ultimately determining the liquefaction temperature of the insulating gas. Therefore, this example predicts the liquefaction temperature of a gas based on molecular force field fitting.

[0064] S700, the amorphous unit cells of multiple gas molecules to be tested are introduced into the optimal liquefaction temperature prediction model to perform heating and cooling simulations, obtain the liquefaction temperature curve, and obtain the liquefaction temperature range based on the liquefaction temperature curve.

[0065] The following steps are included when performing a temperature rise simulation:

[0066] S711, initialize the energy of the optimal liquefaction temperature prediction model, and bring the amorphous unit cells of multiple gas molecules to be tested into the optimal liquefaction temperature prediction model after energy initialization.

[0067] In this embodiment, the amorphous unit cells of 1000 C4F7N molecules are incorporated into the optimal liquefaction temperature prediction model after energy initialization.

[0068] S712, under a canonical ensemble, sets the initial temperature and heating step size to construct a dynamic simulation environment.

[0069] S713, at the initial temperature, for each heating step increase, a molecular dynamics simulation is performed on the environment where the optimal liquefaction temperature prediction model is located, and the stable structure at this temperature is obtained, and the density of the environment where the optimal liquefaction temperature prediction model is located at this temperature is recorded.

[0070] S714, Repeat step S713 until the liquid system of the gas molecules to be tested boils and completely vaporizes. The density mutation point during the gradual heating process will be determined, and the first mutation temperature at this time will be recorded.

[0071] The cooling simulation includes the following steps:

[0072] S721 sets the cooling step size, and gradually cools down after the gas molecules to be measured have completely vaporized.

[0073] S722 performs a molecular dynamics simulation on the environment of the optimal liquefaction temperature prediction model for each cooling step size, obtains the stable structure at this temperature, and records the density of the environment of the optimal liquefaction temperature prediction model at this temperature.

[0074] S723, repeat step S722 until the gaseous system of the gas molecules to be tested is completely liquefied, determine the density abrupt change point during the gradual cooling process, and record the second abrupt change temperature at this time.

[0075] Specifically, the initial temperature is 260K, the temperature increment is 1K, and the duration of each temperature setting during the simulation is 1000ps, with a total simulation duration of 11ns. The cooling increment is equal to the heating increment.

[0076] The density data obtained during the heating simulation and the density data obtained during the cooling simulation are used to plot a liquefaction temperature curve. In the liquefaction temperature curve, the first abrupt change temperature and the second abrupt change temperature are phase transition temperatures; that is, the range between the first abrupt change temperature and the second abrupt change temperature is the liquefaction temperature range. Please refer to [link / reference]. Figure 3 Therefore, the liquefaction temperature of C4F7N molecules predicted by this invention is between 266K and 268K, while the liquefaction temperature of C4F7N molecules obtained from the literature is 268K, which means that the prediction accuracy of this invention is high.

[0077] Example 2

[0078] Please see Figures 1 to 4 As shown, the difference from Example 1 is that the gas in this example is a mixed gas, specifically C4F7N / CO2. In this example, an amorphous unit cell containing 20 C4F7N molecules and 100 CO2 molecules is constructed in the initial environment to obtain the initial C4F7N / CO2 crystal structure. When calculating the density of the gas crystal structure in the molecular mechanics environment and the gas crystal structure in the force field energy environment, m is the mass of the C4F7N crystal. Specifically, when inputting the amorphous unit cell of the gas molecules to be tested, it is a mixed gas amorphous unit cell containing 200 C4F7N molecules and 1000 CO2 molecules. See also... Figure 4Therefore, the liquefaction temperature of the C4F7N / CO2 molecule predicted by this invention is between 242K and 244K.

[0079] Example 3

[0080] Please see Figures 1 to 6 As shown, the difference between this embodiment and embodiments 1 and 2 is that the gas in this embodiment is water vapor. In the gas liquefaction temperature prediction method, the order of the heating simulation and the cooling simulation is not important and can be interchanged. In embodiments 1 and 2, the heating simulation is performed first, followed by the cooling simulation. In this embodiment, the cooling simulation is performed first, followed by the heating simulation, ultimately obtaining the liquefaction temperature curve as shown. Figure 6 As shown, the predicted liquefaction temperature is 371–373 K.

[0081] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered illustrative and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention, and no reference numerals in the claims should be construed as limiting the scope of the claims.

[0082] The above embodiments are merely examples of implementation methods of the invention. The scope of protection of the present invention is not limited to the above embodiments. For those skilled in the art, several modifications and improvements can be made without departing from the concept of the present invention, and these all fall within the scope of protection of the present invention.

Claims

1. A method for predicting the liquefaction temperature of a gas, characterized in that, Includes the following steps: S100, establish an amorphous unit cell for multiple gas molecules to obtain the initial gas crystal structure; S200, based on density functional theory, optimizes the bonding parameters and unit cell parameters of the initial gas crystal structure to obtain a stable molecular mechanical environment gas crystal structure; S300, using the Compass II force field, performs energy initialization on the initial gas crystal structure to obtain a stable force field energy environment gas crystal structure; S400, calculate the average interaction force and density of each single molecule in the molecular mechanical environment gas crystal structure and the force field energy environment gas crystal structure, respectively; S500, compare the average interaction forces and densities of the molecular mechanical environment gas crystal structure and the force field energy environment gas crystal structure respectively to obtain the initial liquefaction temperature prediction model; S600, continuously adjust the force field parameters of the Compass II force field of the initial gas crystal structure in the initial liquefaction temperature prediction model, update the initial liquefaction temperature prediction model, and obtain the best-fitting liquefaction temperature prediction model, including: Each time the force field parameters of the initial gas crystal structure are adjusted, the initial liquefaction temperature prediction model is updated. Each time it is updated, the initial gas crystal structure is initialized with energy and the corresponding average interaction force and density are calculated until the average interaction force and density are close to those of the gas crystal structure in the molecular mechanical environment. The liquefaction temperature prediction model fitted at this time is the optimal liquefaction temperature prediction model. S700, the amorphous unit cells of multiple gas molecules to be tested are introduced into the optimal liquefaction temperature prediction model to perform heating and cooling simulations, obtain the liquefaction temperature curve, and obtain the liquefaction temperature range based on the liquefaction temperature curve.

2. The gas liquefaction temperature prediction method according to claim 1, characterized in that, The average interaction force is obtained by the following formula: ； In the formula, For the average interaction force, The total energy of the gas crystal. The energy of a single molecule, This represents the number of molecules.

3. The gas liquefaction temperature prediction method according to claim 1, characterized in that, The similarity criterion is that the average interaction force and density calculated from the updated gas crystal structure have an error of less than 2% compared with the average interaction force and density of the gas crystal structure in the molecular mechanical environment.

4. The gas liquefaction temperature prediction method according to claim 1, characterized in that, The following steps are included when performing a temperature rise simulation: S711, initialize the energy of the optimal liquefaction temperature prediction model, and bring the amorphous unit cells of multiple gas molecules to be tested into the optimal liquefaction temperature prediction model after energy initialization. S712, under a canonical ensemble, sets the initial temperature and heating step size to construct a dynamic simulation environment; S713, at the initial temperature, for each heating step increase, a molecular dynamics simulation is performed on the environment where the optimal liquefaction temperature prediction model is located, and the stable structure at this temperature is obtained, and the density of the environment where the optimal liquefaction temperature prediction model is located at this temperature is recorded. S714, Repeat step S713 until the liquid system of the gas molecules to be tested boils and completely vaporizes. The density mutation point during the gradual heating process will be determined, and the first mutation temperature at this time will be recorded.

5. The gas liquefaction temperature prediction method according to claim 4, characterized in that, The cooling simulation includes the following steps: S721, set the cooling step size, and gradually cool down after the gas molecules to be measured are completely vaporized; S722: For each cooling step decrease, a molecular dynamics simulation is performed on the environment of the optimal liquefaction temperature prediction model, and the stable structure at this temperature is obtained. The density of the environment of the optimal liquefaction temperature prediction model at this temperature is also recorded. S723, repeat step S722 until the gaseous system of the gas molecules to be tested is completely liquefied, determine the density abrupt change point during the gradual cooling process, and record the second abrupt change temperature at this time.

6. The gas liquefaction temperature prediction method according to claim 5, characterized in that, The density data obtained during the heating simulation and the density data obtained during the cooling simulation are used to plot a liquefaction temperature curve; in the liquefaction temperature curve, the range between the first abrupt change temperature and the second abrupt change temperature is the liquefaction temperature range.

7. The gas liquefaction temperature prediction method according to claim 5, characterized in that, The cooling step size is equal to the heating step size.

8. The gas liquefaction temperature prediction method according to claim 5, characterized in that, The order of the heating simulation and the cooling simulation is not important.

9. The gas liquefaction temperature prediction method according to claim 6, characterized in that, The first mutation temperature and the second mutation temperature are phase transition temperatures.

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