Method and device for determining thermal conductivity of chloride molten salt

Abstract

The invention discloses a method and a device for determining the heat conductivity of chloride molten salt, relates to the technical field of molecular dynamics simulation and photovoltaic heat storage, and mainly aims to solve the problem that the accuracy of determining the heat conductivity of the chloride molten salt at a high-temperature section (1,400 K and above) is relatively low. The method mainly comprises the steps that molten salt parameters of target chloride molten salt are obtained, preset temperature control conditions matched with the target chloride molten salt are obtained, and the target chloride molten salt is single-component chloride molten salt or mixed chloride molten salt; building chloride molten salt elementary substance unit cells according to the molten salt parameters, and building a target molecular model based on the chloride molten salt elementary substance unit cells; according to a target potential function and the preset temperature control condition, reverse non-equilibrium molecular dynamics simulation is carried out on the heat conduction process of a target molecular model, and temperature gradient and molecular kinetic energy data are obtained; and calculating the thermal conductivity of the target chloride fused salt according to the temperature gradient and the molecular kinetic energy data. The method is mainly used for determining the thermal conductivity of chloride molten salt.

Description

Technical Field

[0001] The invention relates to the technical field of molecular dynamics simulation and photovoltaic heat storage, and in particular to a method and device for determining the thermal conductivity of a chloride molten salt. Background Art

[0002] Molten salt heat storage is a technology that uses the temperature difference of molten salt during the heating and cooling process to achieve thermal energy storage. As a heat storage medium with low cost, stable working state, high heat storage density and long heat storage time, molten salt occupies a major position in large-scale medium and high temperature heat storage projects, such as concentrated solar thermal power generation, thermal power plant transformation and other new long-term heat storage. With the development of heat storage technology, the requirements for the working temperature of molten salt are getting higher and higher. Chloride molten salt, as a heat storage medium with a higher applicable temperature than alkali metal molten salt, has become the focus of research in this field.

[0003] Existing equipment for evaluating the thermal properties of molten salts mainly uses scanning calorimeters for testing, but the temperature measurement range of such equipment is usually below 650°C, while the melting point of commonly used chloride molten salts is around 1100K, resulting in a lack of thermal conductivity data for chloride molten salts in the high temperature range, which greatly reduces the accuracy of the thermal conductivity evaluation of chloride molten salts. Therefore, there is an urgent need for a method to accurately evaluate the thermal conductivity of chloride molten salts. Summary of the invention

[0004] In view of this, the present invention provides a method and device for determining the thermal conductivity of chloride molten salt, the main purpose of which is to solve the problem of low accuracy in evaluating the thermal conductivity of existing chloride molten salts.

[0005] According to one aspect of the present invention, a method for determining thermal conductivity of a chloride molten salt is provided, comprising:

[0006] Acquiring molten salt parameters of a target chloride molten salt and matching preset temperature control conditions of the target chloride molten salt, wherein the target chloride molten salt is a single-component chloride molten salt or a mixed chloride molten salt;

[0007] Constructing a chloride molten salt unit cell according to the molten salt parameters, and obtaining a target molecular model based on the chloride molten salt unit cell;

[0008] According to the target potential function and the preset temperature control conditions, a reverse non-equilibrium molecular dynamics simulation is performed on the heat conduction process of the target molecular model to obtain temperature gradient and molecular kinetic energy data;

[0009] The thermal conductivity of the target chloride molten salt is calculated based on the temperature gradient and the molecular kinetic energy data.

[0010] Furthermore, the target molecular model is constructed based on the chloride molten salt single substance unit cell, comprising:

[0011] Expanding the chloride molten salt single-substance unit cell to a preset number of molecules to obtain an initial molecular model;

[0012] Performing annealing treatment on the initial molecular model;

[0013] The initial molecular model after annealing is subjected to lattice optimization to obtain a target molecular model.

[0014] Further, in the case where the target chloride molten salt is a mixed chloride molten salt, the chloride molten salt single substance unit cell includes chloride molten salt single substance unit cells of different chlorides, and the chloride molten salt single substance unit cell is expanded to a preset number of molecules to obtain an initial molecular model, including:

[0015] According to the ratio between different chlorides in the molten salt parameters, the single-substance unit cells of the chloride molten salt with different chlorides are expanded until the total amount of the single-substance unit cells of the chloride molten salt with different chlorides meets the preset number of molecules, thereby obtaining an initial molecular model.

[0016] Furthermore, the preset temperature control conditions include a limit heating temperature, a target simulation temperature, a first duration, and a second duration. According to the target potential function and the preset temperature control conditions, a reverse non-equilibrium molecular dynamics simulation is performed on the heat conduction process of the target molecular model to obtain temperature gradient and molecular kinetic energy data, including:

[0017] Extracting model system coordinate information and charge information from the target molecule model, and constructing a three-dimensional cubic box based on the model system coordinate information, wherein the three-dimensional cubic box is used to characterize the periodic boundary conditions of the simulation process;

[0018] Simulating a heat bath heating under a canonical ensemble, raising the temperature to the limit heating temperature so that the target chloride molten salt is in a molten state, and cooling to the target simulation temperature;

[0019] The first time duration is balanced in an isothermal and isobaric ensemble and a canonical ensemble in turn, and during the balancing process, the position and velocity of the particle in the three-dimensional cubic box are updated according to the target potential function and the charge information;

[0020] The temperature gradient and molecular kinetic energy data in the three-dimensional cubic box are extracted under the microcanonical ensemble.

[0021] Further, updating the position and velocity of the particles in the three-dimensional cubic box according to the target potential function includes:

[0022] The charge information is loaded into the target potential function, and the short-range interaction force is solved by using the truncation method according to a preset truncation radius, and the long-range electrostatic interaction force is solved by using the Ewald algorithm according to a preset calculation accuracy;

[0023] Initializing the particle acceleration according to the short-range interaction force and the long-range electrostatic interaction force, and constructing Newton's motion equation according to the initialized particle acceleration and preset environmental parameters, wherein the preset environmental parameters include pressure value, stress damping coefficient, temperature damping coefficient and energy exchange rate;

[0024] The Velocity-Verlet algorithm is used to solve the Newtonian equations of motion to update the positions and velocities of the particles in the three-dimensional cubic box.

[0025] Furthermore, the formula of the target potential function is:

[0026] Among them, q i represents the formal charge of the alkali metal ion, which is +1; q j represents the formal charge of the chloride ion, which is -1; r ij is the center distance between the two ions, A ij represents the exclusion parameter; σ ij represents the ionic radius of the crystal, ρ represents the hardness parameter, C ij and D ij represents the van der Waals parameter.

[0027] Furthermore, the pressure value is 0.1 MPa and the preset interception radius is The preset calculation accuracy is 1×10 -4 , the stress damping coefficient is 1000, the temperature damping coefficient is 100, and the energy exchange rate is 200.

[0028] Furthermore, the target chloride molten salt is the energy storage material to be verified for the target energy storage device, the target simulation temperature is determined based on the expected operating environment of the target energy storage device, the limit heating temperature has a value range of [1800K, 2000K], the first time length is 0.1ns, and the second time length is 1ns.

[0029] Furthermore, after calculating the thermal conductivity of the target chloride molten salt according to the temperature gradient and the molecular kinetic energy data, the method further includes:

[0030] Retrieving a candidate chloride molten salt sequence of the target energy storage device, wherein the candidate chloride molten salt sequence is obtained by sorting the thermal conductivities of different previously verified candidate chloride molten salts;

[0031] The rank of the target chloride molten salt in the candidate chloride molten salt sequence is determined according to the thermal conductivity, and the target chloride molten salt is updated to the candidate chloride molten salt sequence according to the rank.

[0032] According to another aspect of the present invention, a device for determining thermal conductivity of a chloride molten salt is provided, comprising:

[0033] An acquisition module is used to acquire molten salt parameters of a target chloride molten salt, and match a target potential function and preset temperature control conditions of the target chloride molten salt, wherein the target chloride molten salt is a single-component chloride molten salt or a mixed chloride molten salt;

[0034] A construction module, used to construct a chloride molten salt single substance unit cell according to the molten salt parameters, and obtain a target molecular model based on the chloride molten salt single substance unit cell;

[0035] A simulation module, for performing a reverse non-equilibrium molecular dynamics simulation on the heat conduction process of the target molecular model according to the target potential function and the preset temperature control conditions, to obtain temperature gradient and molecular kinetic energy data;

[0036] A calculation module is used to calculate the thermal conductivity of the target chloride molten salt according to the temperature gradient and the molecular kinetic energy data.

[0037] Furthermore, the building block includes:

[0038] An expansion unit, used to expand the chloride molten salt single substance unit cell to a preset number of molecules to obtain an initial molecular model;

[0039] An annealing unit, used for performing annealing on the initial molecular model;

[0040] The lattice optimization unit is used to perform lattice optimization on the initial molecular model after annealing to obtain a target molecular model.

[0041] Furthermore, in a specific application scenario, the expansion unit is specifically used to expand the chloride molten salt single-substance crystal cells of different chlorides according to the ratio between different chlorides in the molten salt parameters, until the total amount of the chloride molten salt single-substance crystal cells of different chlorides meets the preset number of molecules, thereby obtaining an initial molecular model.

[0042] Furthermore, the simulation module includes:

[0043] A construction unit, used to extract model system coordinate information and charge information in the target molecule model, and to construct a three-dimensional cubic box according to the model system coordinate information, wherein the three-dimensional cubic box is used to characterize the periodic boundary conditions of the simulation process;

[0044] A temperature control unit is used to simulate the heating of a hot bath under a canonical ensemble, raise the temperature to the limit heating temperature so that the target chloride molten salt is in a molten state, and cool it to the target simulation temperature;

[0045] An updating unit, used to balance the first time length in an isothermal and isobaric ensemble and a canonical ensemble in turn, and in the balancing process, update the position and velocity of the particles in the three-dimensional cubic box according to the target potential function and the charge information;

[0046] The extraction unit is used to extract the temperature gradient and molecular kinetic energy data in the three-dimensional cubic box under the microcanonical ensemble.

[0047] Further, in a specific application scenario, the updating unit is specifically used to load the charge information into the target potential function, and solve the short-range interaction force according to a preset interception radius using a truncation method, and solve the long-range electrostatic interaction force according to a preset calculation accuracy using an Ewald algorithm;

[0048] Initializing the particle acceleration according to the short-range interaction force and the long-range electrostatic interaction force, and constructing Newton's motion equation according to the initialized particle acceleration and preset environmental parameters, wherein the preset environmental parameters include pressure value, stress damping coefficient, temperature damping coefficient and energy exchange rate;

[0049] The Velocity-Verlet algorithm is used to solve the Newtonian equations of motion to update the positions and velocities of the particles in the three-dimensional cubic box.

[0050] Furthermore, the formula of the target potential function is:

[0051] Among them, q i represents the formal charge of the alkali metal ion, which is +1; q j represents the formal charge of the chloride ion, which is -1; r ij is the center distance between the two ions, A ij represents the exclusion parameter; σ ij represents the ionic radius of the crystal, ρ represents the hardness parameter, C ij and D ij represents the van der Waals parameter.

[0052] Furthermore, in a specific application scenario, the pressure value is 0.1 MPa and the preset interception radius is The preset calculation accuracy is 1×10 -4 , the stress damping coefficient is 1000, the temperature damping coefficient is 100, and the energy exchange rate is 200.

[0053] Furthermore, in a specific application scenario, the target chloride molten salt is the energy storage material to be verified for the target energy storage device, the target simulation temperature is determined based on the expected operating environment of the target energy storage device, the limit heating temperature has a value range of [1800K, 2000K], the first time length is 0.1ns, and the second time length is 1ns.

[0054] Furthermore, the module also includes:

[0055] A calling module, used for calling a candidate chloride molten salt sequence of the target energy storage device, wherein the candidate chloride molten salt sequence is obtained by sorting the thermal conductivity of different candidate chloride molten salts that have been verified previously;

[0056] An updating module is used to determine the rank of the target chloride molten salt in the sequence of candidate chloride molten salts according to the thermal conductivity, and update the target chloride molten salt to the sequence of candidate chloride molten salts according to the rank.

[0057] By means of the above technical solution, the technical solution provided by the embodiment of the present invention has at least the following advantages:

[0058] The present invention provides a method and device for determining the thermal conductivity of a chloride molten salt. In an embodiment of the present invention, molten salt parameters of a target chloride molten salt are obtained, and preset temperature control conditions of the target chloride molten salt are matched, wherein the target chloride molten salt is a single-component chloride molten salt or a mixed chloride molten salt; a single-substance unit cell of the chloride molten salt is constructed according to the molten salt parameters, and a target molecular model is obtained based on the single-substance unit cell of the chloride molten salt; according to a target potential function and the preset temperature control conditions, a reverse non-equilibrium molecular dynamics simulation is performed on the heat conduction process of the target molecular model to obtain a temperature gradient and molecular kinetic energy data; and the thermal conductivity of the target chloride molten salt is calculated according to the temperature gradient and the molecular kinetic energy data. Without any actual experiments, the temperature gradient and molecular kinetic energy data can be accurately simulated to obtain the thermal conductivity of chloride molten salt and its mixture, which greatly reduces the experimental cost and solves the problem of lack of experimental data in the high temperature section (1400K and above) of chloride molten salt. At the same time, the thermal conductivity of chloride molten salt can be evaluated in multiple temperature sections, thereby improving the accuracy of the thermal conductivity evaluation of chloride molten salt.

[0059] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0061] Figure 1 A flow chart of a method for determining thermal conductivity of a chloride molten salt provided by an embodiment of the present invention is shown;

[0062] Figure 2 A flow chart of another method for determining thermal conductivity of a chloride molten salt provided by an embodiment of the present invention is shown;

[0063] Figure 3 A block diagram of the composition of a device for determining thermal conductivity of a chloride molten salt provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0064] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0065] In view of the low accuracy of thermal conductivity test of existing chloride molten salt, the present invention provides a method for determining thermal conductivity of chloride molten salt, such as Figure 1 As shown, the method includes:

[0066] 101. Obtain molten salt parameters of a target chloride molten salt, and match preset temperature control conditions of the target chloride molten salt.

[0067] In an embodiment of the present invention, the target chloride molten salt is a single-component chloride molten salt or a mixed chloride molten salt. Wherein, the single-component chloride molten salt can be one of LiCl, KCl, and NaCl single substances, and the mixed chloride molten salt can be a mixture of any two or three of LiCl, KCl, and NaCl single substances. The molten salt parameters include the ion composition and concentration of the target chloride molten salt, and the ratio of different compounds when the target chloride molten salt is a mixed chloride molten salt. The preset temperature control condition is determined according to the melting point temperature of the target chloride molten salt, and the expected temperature to be simulated can include the limit heating temperature, the target simulation temperature, and the equilibrium time under different ensembles.

[0068] 102. Construct a chloride molten salt unit cell according to the molten salt parameters, and obtain a target molecular model based on the chloride molten salt unit cell.

[0069] In the embodiment of the present invention, according to the molten salt parameters such as ion composition and concentration of the target chloride molten salt, Diamond software is called to build a chloride molten salt single substance unit cell, and the chloride molten salt single substance unit cell is imported into Packmol software, so that the chloride molten salt single substance unit cell is expanded based on Packmol software, and an initial molecular model is constructed, and then the model is optimized according to the initial molecular model to obtain a model architecture, i.e., a target molecular model. By constructing a chloride molten salt single substance unit cell, and then constructing a target molecular model according to the chloride molten salt single substance unit cell, the molecular model can more realistically reflect the atomic distribution of the target chloride molten salt, thereby improving the accuracy of subsequent molecular dynamics simulations.

[0070] 103. According to the target potential function and the preset temperature control conditions, a reverse non-equilibrium molecular dynamics simulation is performed on the heat conduction process of the target molecular model to obtain temperature gradient and molecular kinetic energy data.

[0071] In an embodiment of the present invention, the target potential function is a potential function constructed based on the Born-Mayer-Huggins potential, which is used to characterize the interaction between ions in the target chloride molten salt. The parameters of the target potential function are determined based on the target chloride molten salt compound composition. Reverse Nonequilibrium Molecular Dynamics (RNEMD) is a molecular dynamics simulation method for calculating material properties. According to this method, the model system is divided into multiple boundary regions, and the speed or energy of the atoms in the boundary region is adjusted according to the preset temperature control conditions to realize the simulation process. When the movement of atoms presents a dynamic equilibrium, the temperature gradient and molecular kinetic energy data are extracted. The heat conduction process of the target chloride molten salt is simulated by reverse non-equilibrium molecular dynamics, and the heat conduction simulation under high temperature state can be realized according to the temperature simulation requirements. At the same time, the temperature gradient and molecular kinetic energy data can be accurately simulated, providing accurate data basis for the calculation of thermal conductivity.

[0072] 104. Calculate the thermal conductivity of the target chloride molten salt according to the temperature gradient and the molecular kinetic energy data.

[0073] In the embodiment of the present invention, the temperature gradient is the temperature gradient of the molecular dynamics simulation system along the Z direction, and the molecular kinetic energy data includes the molecular kinetic energy of the hot source area and the cold source area. After the temperature gradient and molecular kinetic energy data are obtained by reverse non-equilibrium molecular dynamics simulation, the thermal conductivity of the target chloride molten salt is calculated by Fourier's law according to the parameters of the simulation system. The thermal conductivity is set to λ, and the thermal conductivity calculation formula is:

[0074]

[0075] in, It represents the kinetic energy of the molecules in the heat source area; represents the kinetic energy of the molecules in the cold source area; t represents the exchange time; L x represents the length of the molecular dynamics simulation system along the X direction; L y represents the length of the molecular dynamics simulation system along the Y direction; Represents the temperature gradient of the molecular dynamics simulation system along the Z direction.

[0076] It should be noted that by constructing a single unit cell of chloride molten salt and constructing a molecular model based on the single unit cell of chloride molten salt, the atomic distribution of the molecular model can be made more consistent with the actual molecular state. Through the reverse non-equilibrium molecular dynamics method, thermal conductivity simulation is performed according to preset temperature control conditions, which can simulate the temperature that is difficult to reach in actual measurement, overcome the difficulties in creating a real temperature environment and the inaccuracy of actual testing. While meeting the thermal conductivity evaluation requirements of chloride molten salt, the temperature gradient and molecular kinetic energy data of the target chloride molten salt at the required simulation temperature are accurately and intuitively displayed, thereby improving the accuracy of the thermal conductivity evaluation of chloride molten salt.

[0077] In an embodiment of the present invention, for further explanation and limitation, as Figure 2 As shown, the step of constructing a target molecular model based on the chloride molten salt single substance unit cell comprises:

[0078] 201. Expand the chloride molten salt single-substance unit cell to a preset number of molecules to obtain an initial molecular model.

[0079] 202. Perform annealing processing on the initial molecular model.

[0080] 203. Perform lattice optimization on the initial molecular model after annealing to obtain a target molecular model.

[0081] In the embodiment of the present invention, the preset number of molecules can be 5000, that is, the chloride molten salt is expanded to 5000 molecules. Of course, the preset number of molecules can also be customized according to actual application requirements, and the embodiment of the present invention is not specifically limited. Specifically, by importing the chloride molten salt single substance unit cell into Packmol software, the molecule is expanded by Packmol software to obtain an initial molecular model. After obtaining the initial molecular model, the initial molecular model is processed and optimized. Specifically including: the chloride molten salt system after Packmol construction is imported into Material Studio, and the relative atomic mass and charge quantity of elements such as Li, Na, K, Cl are marked in the software according to the compound composition of the target chloride molten salt, Forcite module is used and Optimize cell is checked to anneal the initial molecular model and perform lattice optimization, so that the chloride molten salt system energy converges to a minimum value, thereby obtaining the optimized system architecture, i.e., the target molecular model, and output car and mdf files.

[0082] In one embodiment of the present invention, for further explanation and limitation, the chloride molten salt single substance unit cell is expanded to a preset number of molecules to obtain an initial molecular model, including:

[0083] According to the ratio between different chlorides in the molten salt parameters, the single-substance unit cells of the chloride molten salt with different chlorides are expanded until the total amount of the single-substance unit cells of the chloride molten salt with different chlorides meets the preset number of molecules, thereby obtaining an initial molecular model.

[0084] In an embodiment of the present invention, when the target chloride molten salt is a single-component chloride molten salt, the chloride molten salt single-substance unit cell can be directly expanded, and when the target chloride molten salt is a mixed chloride molten salt, the chloride molten salt single-substance unit cell is not a single compound, and includes chloride molten salt single-substance unit cells of different chlorides. It is necessary to uniformly mix and expand the chloride molten salt single-substance unit cells of different chlorides according to the ratio between different chlorides in the molten salt parameters, so that the total amount of the chloride molten salt single-substance unit cells of different chlorides after expansion is equal to the preset number of molecules.

[0085] In one embodiment of the present invention, for further explanation and limitation, the heat conduction process of the target molecular model is subjected to reverse non-equilibrium molecular dynamics simulation based on the target potential function and the preset temperature control condition to obtain the temperature gradient and molecular kinetic energy data, including:

[0086] Extracting model system coordinate information and charge information from the target molecule model, and constructing a three-dimensional cubic box based on the model system coordinate information;

[0087] Simulating a heat bath heating under a canonical ensemble, raising the temperature to the limit heating temperature so that the target chloride molten salt is in a molten state, and cooling to the target simulation temperature;

[0088] The first time duration is balanced in an isothermal and isobaric ensemble and a canonical ensemble in sequence, and during the balancing process, the positions and velocities of atoms in the three-dimensional cubic box are updated according to the target potential function and the charge information;

[0089] The temperature gradient and molecular kinetic energy data in the three-dimensional cubic box are extracted under the microcanonical ensemble.

[0090] In the embodiment of the present invention, the model system coordinates and charge and other related information of the target molecule model are output by the ms2lmp program in the molecular dynamics software lammps and the corresponding command, wherein, the force field selects pcff or cvff. Using a three-dimensional cube box, x, y, z directions are all set to periodic boundary conditions, i.e., the three-dimensional cube box is used to characterize the periodic boundary conditions of the simulation process. The preset temperature control conditions include the limit heating temperature, the target simulation temperature, the first duration and the second duration. Then simulate the system state under different constraints, first warm up to the limit heating temperature under the canonical ensemble, make the chloride molten salt molten state, and then cool it down until the temperature is cooled to the temperature (target simulation temperature) to be simulated. Wherein, the value interval of the limit heating temperature is [1800K, 2000K], preferably, the value of the limit heating temperature is 2000K, the first duration is 100,000 steps, i.e. 0.1ns, and the second duration is 1 million steps, i.e. 1ns. In the case where the target chloride molten salt is the heat storage medium to be verified of the target heat storage device, the target simulation temperature may be determined based on the expected heat storage capacity of the heat storage medium to be verified.

[0091] In order to make the system present dynamic equilibrium, it is necessary to go through a period of equilibrium time in each ensemble. Specifically, the equilibrium time in the isothermal and isobaric ensemble is configured as the first duration, in which the temperature control method selects the Nose-Hover heat bath method, and the pressure and stress damping coefficients are set according to the actual simulation requirements. The equilibrium time in the canonical ensemble is the first duration, and the temperature damping coefficient and energy interaction rate are set. Finally, the temperature gradient and molecular kinetic energy data in the microcanonical ensemble, the equilibrium time in the microcanonical ensemble is configured as the second duration. Among them, the canonical ensemble (NVT: canonical ensemble) is an ensemble that constrains the number of particles, volume and temperature; the isothermal and isobaric ensemble (NPT: isothermal-isobaric ensemble) is an ensemble that constrains the number of particles, pressure and temperature; the microcanonical ensemble (NVE: micro-canonical ensemble) is an ensemble that constrains the number of particles, volume and total energy. It has been verified through experiments that when the pressure value is set to 0.1 MPa, the stress damping coefficient is set to 1000, the temperature damping coefficient is set to 100, and the energy exchange rate is set to 200, the error between the simulation and the actual test value is the smallest. Of course, the above parameters can also be customized according to actual application requirements, and the embodiments of the present invention do not make specific limitations.

[0092] It should be noted that the three-dimensional cubic box is evenly divided into 20 layers, the z=0 plate is defined as plate 1, and z=L / 2 is defined as plate 2 (L is the length of the system along the Z axis). During the simulation, if the hottest atom in plate 1 has higher kinetic energy than the coldest atom in plate 2, the speeds of the two atoms can be interchanged. Kinetic energy is exchanged between the 1st and 11th layers and between the 20th and 11th layers at specific time intervals. Since the 11th layer is used as the boundary, it is necessary to ensure that the temperature gradients on both sides are as close as possible to ensure that the error of the calculated value is smaller. Because there is no other energy involved, according to the law of conservation of energy, the sum of the kinetic energy exchanged during the simulation is the total thermal energy of the system. When dynamic equilibrium is reached, the three-dimensional cubic box (system) will present a linear temperature gradient along the z direction. At the same time, the kinetic energy of the molecules in the heat source area and the cold zone, the energy interaction time, and the length of the three-dimensional cubic box along the X and Y axes can also be extracted. Based on the above extracted data, the thermal conductivity is calculated according to Fourier's law. The problem of lack of experimental data in the high-temperature stage was solved through thermal conductivity simulation. The simulated data can be used to evaluate the thermal conductivity of chloride molten salt in different temperature ranges and used as heat storage materials, thereby improving the comprehensiveness of the thermal conductivity evaluation of chloride molten salt.

[0093] In one embodiment of the present invention, for further explanation and limitation, updating the positions and velocities of atoms in the three-dimensional cubic box according to the target potential function includes:

[0094] The charge information is loaded into the target potential function, and the short-range interaction force is solved by using the truncation method according to a preset truncation radius, and the long-range electrostatic interaction force is solved by using the Ewald algorithm according to a preset calculation accuracy;

[0095] Initializing the atomic acceleration according to the short-range interaction force and the long-range electrostatic interaction force, and constructing Newton's motion equation according to the initialized atomic acceleration and preset environmental parameters;

[0096] The Velocity-Verlet algorithm is used to solve the Newtonian equations of motion to update the positions and velocities of atoms in the three-dimensional cubic box.

[0097] In the embodiment of the present invention, during the reverse non-equilibrium molecular dynamics simulation of heat conduction, the short-range interaction force is solved by the truncation method according to the preset interception radius, and the long-range electrostatic interaction force is solved by the Ewald algorithm according to the preset calculation accuracy. It has been verified by experiments that the preset interception radius is The default calculation accuracy is 1×10 -4 When ensuring the simulation calculation accuracy, the computer operation consumption is minimized. Of course, the interception radius and calculation accuracy can also be customized according to actual application requirements, and the embodiment of the present invention does not make specific limitations. The preset environmental parameters include pressure value, stress damping coefficient, temperature damping coefficient and energy exchange rate, which are parameters configured during the thermal simulation parameter configuration process. The Velocity-Verlet algorithm is used to solve Newton's equation of motion, and the time step is 1fs.

[0098] In one embodiment of the present invention, for further explanation and limitation, the formula of the target potential function is:

[0099]

[0100] Among them, q i represents the formal charge of the alkali metal ion, which is +1; q j represents the formal charge of the chloride ion, which is -1; r ij is the center distance between the two ions, A ij represents the exclusion parameter; σ ij represents the ionic radius of the crystal, ρ represents the hardness parameter, C ij and D ij The parameters in the above potential function can be determined by the corresponding table of potential function parameters of polychloride molten salt (such as Table 1) and the corresponding table of potential function parameters of single chloride molten salt (such as Table 2).

[0101] Table 1:

[0102]

[0103] Table 2:

[0104]

[0105]

[0106] In one embodiment of the present invention, for further explanation and limitation, after calculating the thermal conductivity of the target chloride molten salt according to the temperature gradient and the molecular kinetic energy data, the method further includes:

[0107] Retrieving a candidate chloride molten salt sequence for the target heat storage device;

[0108] The rank of the target chloride molten salt in the candidate chloride molten salt sequence is determined according to the thermal conductivity, and the target chloride molten salt is updated to the candidate chloride molten salt sequence according to the rank.

[0109] In an embodiment of the present invention, the target chloride molten salt is the heat storage medium to be verified for the target heat storage device. During the design and development process of the target heat storage device, it is necessary to evaluate the thermal conductivity of chloride molten salts with different chemical compositions and different ratios to determine a chloride molten salt with the best thermal conductivity as the heat storage medium for the target heat storage device. After each thermal conductivity simulation of a chloride molten salt is completed, the sequence of alternative chloride molten salts is updated to record and display the ranking of the thermal conductivity of the simulated chloride molten salt, so that designers can conveniently and intuitively understand the overall evaluation results of the thermal conductivity of the chloride molten salt. Among them, the sequence of alternative chloride molten salts is obtained based on the ranking of the thermal conductivity of different alternative chloride molten salts that have been verified previously. The sorting order can be from small to large or from large to small, which is not specifically limited in the embodiment of the present invention.

[0110] In an application example, it is necessary to deploy lammps software and a parallel computing environment on a computer or CPU server, build an initial model through Material Studio and lammps, save the atomic information in the data file format, and run the written in file through lammps to simulate heat conduction. Finally, plot, fit and calculate the obtained data to get the final result.

[0111] The present invention provides a method for determining the thermal conductivity of a chloride molten salt. The embodiment of the present invention obtains the molten salt parameters of the target chloride molten salt and matches the preset temperature control conditions of the target chloride molten salt. The target chloride molten salt is a single-component chloride molten salt or a mixed chloride molten salt; a chloride molten salt single-substance unit cell is constructed according to the molten salt parameters, and a target molecular model is constructed based on the chloride molten salt single-substance unit cell; according to the target potential function and the preset temperature control conditions, the heat conduction process of the target molecular model is subjected to reverse non-equilibrium molecular dynamics simulation to obtain temperature gradient and molecular kinetic energy data; the thermal conductivity of the target chloride molten salt is calculated according to the temperature gradient and the molecular kinetic energy data. On the basis of not passing actual experiments throughout the whole process, the temperature gradient and molecular kinetic energy data can be accurately simulated to obtain the thermal conductivity of the chloride molten salt single substance and its mixture, which greatly reduces the experimental cost, solves the problem of lack of experimental data in the high temperature section (1400K and above) of the chloride molten salt, and at the same time, the thermal conductivity of the chloride molten salt can be evaluated in multiple temperature sections, thereby improving the accuracy of the thermal conductivity evaluation of the chloride molten salt.

[0112] Furthermore, as a response to the above Figure 1 The embodiment of the present invention provides a device for determining the thermal conductivity of a chloride molten salt, such as Figure 3 As shown, the device comprises:

[0113] An acquisition module 31 is used to acquire molten salt parameters of a target chloride molten salt, and to match a target potential function and preset temperature control conditions of the target chloride molten salt, wherein the target chloride molten salt is a single-component chloride molten salt or a mixed chloride molten salt;

[0114] A construction module 32 is used to construct a chloride molten salt unit cell according to the molten salt parameters, and obtain a target molecular model based on the chloride molten salt unit cell;

[0115] A simulation module 33 is used to perform a reverse non-equilibrium molecular dynamics simulation on the heat conduction process of the target molecular model according to the target potential function and the preset temperature control condition to obtain temperature gradient and molecular kinetic energy data;

[0116] The calculation module 34 is used to calculate the thermal conductivity of the target chloride molten salt according to the temperature gradient and the molecular kinetic energy data.

[0117] Furthermore, the construction module 32 includes:

[0118] An expansion unit, used to expand the chloride molten salt single substance unit cell to a preset number of molecules to obtain an initial molecular model;

[0119] An annealing unit, used for performing annealing on the initial molecular model;

[0120] The lattice optimization unit is used to perform lattice optimization on the initial molecular model after annealing to obtain a target molecular model.

[0121] Furthermore, in a specific application scenario, the expansion unit is specifically used to expand the chloride molten salt single-substance crystal cells of different chlorides according to the ratio between different chlorides in the molten salt parameters, until the total amount of the chloride molten salt single-substance crystal cells of different chlorides meets the preset number of molecules, thereby obtaining an initial molecular model.

[0122] Furthermore, the simulation module 33 includes:

[0123] A construction unit, used to extract model system coordinate information and charge information in the target molecule model, and to construct a three-dimensional cubic box according to the model system coordinate information, wherein the three-dimensional cubic box is used to characterize the periodic boundary conditions of the simulation process;

[0124] A temperature control unit is used to simulate the heating of a hot bath under a canonical ensemble, raise the temperature to the limit heating temperature so that the target chloride molten salt is in a molten state, and cool it to the target simulation temperature;

[0125] An updating unit, used to balance the first time length in an isothermal and isobaric ensemble and a canonical ensemble in turn, and in the balancing process, update the position and velocity of the particles in the three-dimensional cubic box according to the target potential function and the charge information;

[0126] The extraction unit is used to extract the temperature gradient and molecular kinetic energy data in the three-dimensional cubic box under the microcanonical ensemble.

[0127] Further, in a specific application scenario, the updating unit is specifically used to load the charge information into the target potential function, and solve the short-range interaction force according to a preset interception radius using a truncation method, and solve the long-range electrostatic interaction force according to a preset calculation accuracy using an Ewald algorithm;

[0128] Initializing the particle acceleration according to the short-range interaction force and the long-range electrostatic interaction force, and constructing Newton's motion equation according to the initialized particle acceleration and preset environmental parameters, wherein the preset environmental parameters include pressure value, stress damping coefficient, temperature damping coefficient and energy exchange rate;

[0129] The Velocity-Verlet algorithm is used to solve the Newtonian equations of motion to update the positions and velocities of the particles in the three-dimensional cubic box.

[0130] Furthermore, in a specific application scenario, the formula of the target potential function is:

[0131] Among them, q i represents the formal charge of the alkali metal ion, which is +1; q j represents the formal charge of the chloride ion, which is -1; r ij is the center distance between the two ions, A ij represents the exclusion parameter; σ ij represents the ionic radius of the crystal, ρ represents the hardness parameter, C ij and D ij represents the van der Waals parameter.

[0132] Furthermore, in a specific application scenario, the pressure value is 0.1 MPa and the preset interception radius is The preset calculation accuracy is 1×10 -4 , the stress damping coefficient is 1000, the temperature damping coefficient is 100, and the energy exchange rate is 200.

[0133] Furthermore, in a specific application scenario, the target chloride molten salt is the energy storage material to be verified for the target energy storage device, the target simulation temperature is determined based on the expected operating environment of the target energy storage device, the limit heating temperature has a value range of [1800K, 2000K], the first time length is 0.1ns, and the second time length is 1ns.

[0134] Furthermore, the module also includes:

[0135] A calling module, used for calling a candidate chloride molten salt sequence of the target energy storage device, wherein the candidate chloride molten salt sequence is obtained by sorting the thermal conductivity of different candidate chloride molten salts that have been verified previously;

[0136] An updating module is used to determine the rank of the target chloride molten salt in the sequence of candidate chloride molten salts according to the thermal conductivity, and update the target chloride molten salt to the sequence of candidate chloride molten salts according to the rank.

[0137] The present invention provides a device for determining the thermal conductivity of a chloride molten salt. The embodiment of the present invention obtains the molten salt parameters of the target chloride molten salt and matches the preset temperature control conditions of the target chloride molten salt. The target chloride molten salt is a single-component chloride molten salt or a mixed chloride molten salt; a chloride molten salt single-substance unit cell is constructed according to the molten salt parameters, and a target molecular model is constructed based on the chloride molten salt single-substance unit cell; according to the target potential function and the preset temperature control conditions, the heat conduction process of the target molecular model is subjected to reverse non-equilibrium molecular dynamics simulation to obtain temperature gradient and molecular kinetic energy data; the thermal conductivity of the target chloride molten salt is calculated according to the temperature gradient and the molecular kinetic energy data. On the basis of not passing actual experiments throughout the whole process, the temperature gradient and molecular kinetic energy data can be accurately simulated to obtain the thermal conductivity of the chloride molten salt single substance and its mixture, which greatly reduces the experimental cost, solves the problem of lack of experimental data in the high temperature section (1400K and above) of the chloride molten salt, and at the same time, the thermal conductivity of the chloride molten salt can be evaluated in multiple temperature sections, thereby improving the accuracy of the thermal conductivity evaluation of the chloride molten salt.

[0138] Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, and optionally, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0139] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for determining the thermal conductivity of a chloride molten salt, characterized in that: include: Acquiring molten salt parameters of a target chloride molten salt and matching preset temperature control conditions of the target chloride molten salt, wherein the target chloride molten salt is a single-component chloride molten salt or a mixed chloride molten salt; Constructing a chloride molten salt unit cell according to the molten salt parameters, and obtaining a target molecular model based on the chloride molten salt unit cell; According to the target potential function and the preset temperature control conditions, a reverse non-equilibrium molecular dynamics simulation is performed on the heat conduction process of the target molecular model to obtain temperature gradient and molecular kinetic energy data; The thermal conductivity of the target chloride molten salt is calculated based on the temperature gradient and the molecular kinetic energy data.

2. The method according to claim 1, characterized in that The target molecular model is constructed based on the chloride molten salt single substance unit cell, comprising: Expanding the chloride molten salt single-substance unit cell to a preset number of molecules to obtain an initial molecular model; Performing annealing treatment on the initial molecular model; The initial molecular model after annealing is subjected to lattice optimization to obtain a target molecular model.

3. The method according to claim 2, characterized in that In the case where the target chloride molten salt is a mixed chloride molten salt, the chloride molten salt single substance unit cell includes chloride molten salt single substance unit cells of different chlorides, and the chloride molten salt single substance unit cell is expanded to a preset number of molecules to obtain an initial molecular model, including: According to the ratio between different chlorides in the molten salt parameters, the single-substance unit cells of the chloride molten salt with different chlorides are expanded until the total amount of the single-substance unit cells of the chloride molten salt with different chlorides meets the preset number of molecules, thereby obtaining an initial molecular model.

4. The method according to claim 1, characterized in that: The preset temperature control conditions include a limit heating temperature, a target simulation temperature, a first duration, and a second duration. According to the target potential function and the preset temperature control conditions, a reverse non-equilibrium molecular dynamics simulation is performed on the heat conduction process of the target molecular model to obtain temperature gradient and molecular kinetic energy data, including: Extracting model system coordinate information and charge information from the target molecule model, and constructing a three-dimensional cubic box based on the model system coordinate information, wherein the three-dimensional cubic box is used to characterize the periodic boundary conditions of the simulation process; Simulating a heat bath heating under a canonical ensemble, raising the temperature to the limit heating temperature so that the target chloride molten salt is in a molten state, and cooling to the target simulation temperature; The first time duration is balanced in an isothermal and isobaric ensemble and a canonical ensemble in sequence, and during the balancing process, the positions and velocities of atoms in the three-dimensional cubic box are updated according to the target potential function and the charge information; The temperature gradient and molecular kinetic energy data in the three-dimensional cubic box are extracted under the microcanonical ensemble.

5. The method according to claim 4, characterized in that The updating of the positions and velocities of atoms in the three-dimensional cubic box according to the target potential function comprises: The charge information is loaded into the target potential function, and the short-range interaction force is solved by using the truncation method according to a preset truncation radius, and the long-range electrostatic interaction force is solved by using the Ewald algorithm according to a preset calculation accuracy; Initializing the atomic acceleration according to the short-range interaction force and the long-range electrostatic interaction force, and constructing Newton's motion equation according to the initialized atomic acceleration and preset environmental parameters, wherein the preset environmental parameters include pressure value, stress damping coefficient, temperature damping coefficient and energy exchange rate; The Velocity-Verlet algorithm is used to solve the Newtonian equations of motion to update the positions and velocities of atoms in the three-dimensional cubic box.

6. The method according to claim 4, characterized in that The formula of the objective potential function is: Among them, q i represents the formal charge of the alkali metal ion, which is +1; q j represents the formal charge of the chloride ion, which is -1; r ij is the center distance between the two ions, A ij represents the exclusion parameter; σ ij represents the ionic radius of the crystal, ρ represents the hardness parameter, C ij and D ij represents the van der Waals parameter.

7. The method according to claim 5, characterized in that The pressure value is 0.1 MPa and the preset interception radius is The preset calculation accuracy is 1×10 -4 , the stress damping coefficient is 1000, the temperature damping coefficient is 100, and the energy exchange rate is 200.

8. The method according to any one of claims 1 to 7, characterized in that The target chloride molten salt is the heat storage medium to be verified of the target heat storage device, the target simulation temperature is determined based on the expected design parameters of the target heat storage device, the limit heating temperature has a value range of [1800K, 2000K], the first time length is 0.1ns, and the second time length is 1ns.

9. The method according to claim 8, characterized in that After calculating the thermal conductivity of the target chloride molten salt according to the temperature gradient and the molecular kinetic energy data, the method further includes: Retrieving a candidate chloride molten salt sequence of the target heat storage device, wherein the candidate chloride molten salt sequence is obtained by sorting the thermal conductivities of different previously verified candidate chloride molten salts; The rank of the target chloride molten salt in the candidate chloride molten salt sequence is determined according to the thermal conductivity, and the target chloride molten salt is updated to the candidate chloride molten salt sequence according to the rank.

10. A device for determining thermal conductivity of chloride molten salt, characterized in that: include: An acquisition module is used to acquire molten salt parameters of a target chloride molten salt, and match a target potential function and preset temperature control conditions of the target chloride molten salt, wherein the target chloride molten salt is a single-component chloride molten salt or a mixed chloride molten salt; A construction module, used to construct a chloride molten salt single substance unit cell according to the molten salt parameters, and obtain a target molecular model based on the chloride molten salt single substance unit cell; A simulation module, for performing a reverse non-equilibrium molecular dynamics simulation on the heat conduction process of the target molecular model according to the target potential function and the preset temperature control conditions, to obtain temperature gradient and molecular kinetic energy data; A calculation module is used to calculate the thermal conductivity of the target chloride molten salt according to the temperature gradient and the molecular kinetic energy data.

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