Molecular simulation method for analyzing slow-release process of slow-release agent and slow-release method of slow-release agent

Abstract

The invention provides a molecular simulation method for analyzing a slow-release process of a slow-release agent and a slow-release method of the slow-release agent, and belongs to the technical field of material science and molecular simulation. The molecular simulation method comprises the following steps: respectively simulating adsorption processes and diffusion processes of a plurality of sustained-release agent groups in a target slit hole model by adopting a Monte Carlo method and a molecular dynamics method to obtain competitive adsorption characteristic data and competitive diffusion characteristic data of the plurality of sustained-release agent groups, the sustained-release agent group comprises a main sustained-release agent and a competitive sustained-release agent in different mixing proportions, the target slit hole model is a sustained-release material with a target aperture, and the target aperture gives consideration to adsorption and diffusion of the main sustained-release agent and the competitive sustained-release agent in the sustained-release material; and according to the competitive adsorption characteristic data and the competitive diffusion characteristic data of the plurality of sustained-release agent groups, obtaining sustained-release analysis data of the main sustained-release agent and the competitive sustained-release agent in the target slit hole model.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of material science and molecular simulation, and particularly relates to a molecular simulation method for analyzing a slow-release agent in a slow-release process, a slow-release method of a slow-release agent, and more particularly relates to a method for researching a glycerol slow-release process based on molecular simulation, and a glycerol slow-release method. BACKGROUND

[0002] Slow-release technology has important application value in the fields of medicine, tobacco flavoring, agricultural controlled release, etc. by regulating the adsorption and release kinetics of target molecules. Most traditional slow-release materials rely on physical adsorption of porous structures or bonding of surface chemical groups to achieve molecular loading, but their performance optimization has long been limited by the obscure micro mechanism. Although the current molecular simulation technology can make up for the lack of micro analysis of experiments, it is mostly limited to single adsorption systems, and the simulation accuracy of multi-component co-adsorption systems is insufficient, and the slow-release mechanism has not been systematically and comprehensively analyzed.

[0003] In summary, there is an urgent need for a method that combines multi-scale molecular simulation and experimental verification to reveal the synergistic mechanism between porous materials and slow-release agents at the atomic scale, and to provide a scientific basis for efficient design and performance optimization of slow-release materials. SUMMARY

[0004] To solve the above technical problems, the present application provides a molecular simulation method for analyzing a slow-release agent in a slow-release process, a molecular simulation device thereof, a slow-release method of a slow-release agent, a computing device, a computer readable storage medium, and a computer program product, in order to at least partially solve the above technical problems. To this end, the technical solutions provided by the present application are as follows.

[0005] As a first aspect of the present application, a molecular simulation method for analyzing a slow-release agent in a slow-release process is provided, comprising:

[0006] The Monte Carlo method is used to simulate the adsorption process of each of a plurality of slow-release agent groups in a target slit pore model, to obtain competitive adsorption characteristic data of each of the plurality of slow-release agent groups, wherein the slow-release agent group includes a main slow-release agent and a competitive slow-release agent, the ratio between the main slow-release agent and the competitive slow-release agent in different slow-release agent groups is different, the target slit pore model is a slow-release material with a target pore size, the target pore size takes into account the adsorption and diffusion of the main slow-release agent and the competitive slow-release agent in the slow-release material, and the competitive adsorption characteristic data includes first adsorption characteristic data of the main slow-release agent and the competitive slow-release agent;

[0007] The molecular dynamics method is used to simulate the diffusion process of each of the plurality of slow-release agent groups in the target slit pore model, to obtain competitive diffusion characteristic data of each of the plurality of slow-release agent groups, and the competitive diffusion characteristic data includes first diffusion characteristic data of the main slow-release agent and the competitive slow-release agent;

[0008] According to the competitive adsorption characteristic data and the competitive diffusion characteristic data of each of the plurality of sustained-release agent groups, release analysis data of the main sustained-release agent and the competitive sustained-release agent in the target slit pore model is obtained.

[0009] As a second aspect of the present application, a method for analyzing the release of a sustained-release agent is provided, comprising: determining a target pore size and a target ratio based on the above-mentioned molecular simulation method for analyzing the release of a sustained-release agent in a release process; using a sustained-release material with the target pore size as an adsorption carrier; mixing the main sustained-release agent and the competitive sustained-release agent according to the target ratio, and then adding them to the adsorption carrier for adsorption and diffusion; and testing the release rate of the main sustained-release agent in the adsorption carrier.

[0010] According to a third aspect of the present application, a device for analyzing the release of a sustained-release agent is provided, comprising: an adsorption simulation module, a diffusion simulation module, and a data analysis module.

[0011] The adsorption simulation module comprises a first adsorption simulation module, which is adapted to simulate the adsorption process of each of a plurality of sustained-release agent groups in a target slit pore model by using a Monte Carlo method, to obtain competitive adsorption characteristic data of each of the plurality of sustained-release agent groups, wherein the sustained-release agent groups comprise a main sustained-release agent and a competitive sustained-release agent, the ratio of the main sustained-release agent to the competitive sustained-release agent is different in different sustained-release agent groups, the target slit pore model is a sustained-release material with a target pore size, the target pore size takes into account the adsorption and diffusion of the main sustained-release agent and the competitive sustained-release agent in the sustained-release material, and the competitive adsorption characteristic data comprises first adsorption characteristic data of the main sustained-release agent and the competitive sustained-release agent.

[0012] The diffusion simulation module comprises a first diffusion simulation module, which is adapted to simulate the diffusion process of each of the plurality of sustained-release agent groups in the target slit pore model by using a molecular dynamics method, to obtain competitive diffusion characteristic data of each of the plurality of sustained-release agent groups, wherein the competitive diffusion characteristic data comprises first diffusion characteristic data of the main sustained-release agent and the competitive sustained-release agent.

[0013] The data analysis module comprises a first data analysis submodule, which is adapted to obtain release analysis data of the main sustained-release agent and the competitive sustained-release agent in the target slit pore model according to the competitive adsorption characteristic data and the competitive diffusion characteristic data of each of the plurality of sustained-release agent groups.

[0014] As a fourth aspect of the present application, a computing device is provided, comprising: one or more processors; and a memory for storing one or more computer programs; wherein the one or more processors execute the one or more computer programs to implement the above-mentioned molecular simulation method.

[0015] As a fifth aspect of the present application, a computer readable storage medium is provided, which stores a computer program or executable instructions, which, when executed by a processor, implement the molecular simulation method described above.

[0016] As a sixth aspect of the present application, a computer program product is provided, which comprises a computer program, which, when executed by a processor, implements the molecular simulation method described above.

[0017] In the technical solution of the present application, the adsorption process and diffusion process of each of the multiple slow-release agent groups in the target slit pore model (i.e. slow-release material) are simulated by the molecular simulation method. The obtained competitive adsorption characteristic data is used to characterize the adsorption behavior of the slow-release agent groups in the slow-release material with the target pore size. Similarly, the obtained competitive diffusion characteristic data is used to characterize the diffusion behavior of the slow-release agent groups in the slow-release material with the target pore size. According to the competitive adsorption characteristic data and the competitive diffusion characteristic data, slow-release analysis data of the multiple slow-release agent groups in the target slit pore model can be obtained. According to the slow-release analysis data, the slow-release relationship between the slow-release material with the target pore size and the slow-release agent groups can be clarified, which lays a foundation for designing slow-release materials with higher slow-release performance. The use amount of each slow-release agent in the slow-release group can also be determined, thereby improving the slow-release effect of the slow-release material. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 An application scenario diagram of the molecular simulation method for analyzing the slow-release process of a slow-release agent according to an embodiment of the present application is shown;

[0019] Figure 2 A flowchart of the molecular simulation method for analyzing the slow-release process of a slow-release agent according to an embodiment of the present application is shown;

[0020] Figure 3 A flowchart of the molecular simulation method for analyzing the slow-release process of glycerol in a diatomite slit pore model according to the present application is shown;

[0021] Figure 4 An adsorption isotherm diagram of pure glycerol molecules in diatomite slit pore models with different pore sizes according to an embodiment of the present application is shown;

[0022] Figure 5 An adsorption energy distribution diagram of pure glycerol molecules in diatomite slit pore models with different pore sizes according to an embodiment of the present application is shown;

[0023] Figure 6 A diffusion behavior diagram of pure glycerol molecules in diatomite slit pore models with different pore sizes according to an embodiment of the present application is shown, in which (a) is a mean square displacement diagram, and (b) is a velocity field distribution diagram of pure glycerol molecules perpendicular to the direction of the slit pores of diatomite with different pore sizes;

[0024] Figure 7 Electrostatic field distribution of pure glycerol molecules in a slit pore model of diatomite with a pore size of 7 A for an embodiment of the present application;

[0025] Figure 8 Adsorption density of glycerol and polyethylene glycol with different mixing ratios in a slit pore model of diatomite for an embodiment of the present application;

[0026] Figure 9 Energy distribution of the interaction of glycerol and polyethylene glycol with different mixing ratios on the surface of a slit pore model of diatomite for an embodiment of the present application;

[0027] Figure 10 Kinetic diffusion curve of glycerol and polyethylene glycol with different mixing ratios in a slit pore model of diatomite for an embodiment of the present application;

[0028] Figure 11 Lateral comparison of Figure 10

[0029] Figure 12 Structure block diagram of a molecular simulation device for analyzing the release of a sustained-release agent during a release process for an embodiment of the present application;

[0030] Figure 13 Block diagram of a computing device suitable for implementing a molecular simulation method for analyzing the release of a sustained-release agent during a release process for an embodiment of the present application. DETAILED DESCRIPTION

[0031] Hereinafter, embodiments of the present application will be described with reference to the accompanying drawings. It should be understood, however, that the description which follows is merely exemplary and is not intended to limit the scope of the application. In the following detailed description of embodiments of the present application, numerous specific details are set forth in order to provide a thorough understanding of the present application. However, it will be apparent to one skilled in the art that one or more embodiments of the present application can be practiced without these specific details. In other instances, well-known structures and functions have not been described in detail in order to avoid obscuring aspects of the present application.

[0032] ​Porous slow-release materials (e.g., diatomite, activated carbon, zeolite, molecular sieve, metal-organic framework, etc.) are widely used due to their high specific surface area, chemical stability, and low cost, but their slow-release efficiency and control accuracy still face challenges: on the one hand, experimental methods can characterize the macroscopic adsorption capacity, but it is difficult to reveal the key mechanisms such as hydrogen bond network formation and slow-release agent diffusion path from the microscopic atomic scale; on the other hand, the influence of the pore size of the porous slow-release material on the slow-release performance of the slow-release agent presents non-monotonicity, and the traditional empirical assumption that 'the larger the pore size, the better the diffusion performance' cannot explain this phenomenon, resulting in a lack of theoretical guidance for the design of porous slow-release materials. In addition, the interaction between the slow-release agent and the porous slow-release material, as well as the interaction mechanism between the main slow-release agent and the competitive slow-release agent in the slow-release agent group are not clear, which limits the development of slow-release materials with higher performance and the improvement of slow-release performance.

[0033] To this end, the present application provides a molecular simulation method for analyzing the slow-release process of a slow-release agent, a slow-release method of a slow-release agent, a computing device, a computer-readable storage medium, and a computer program product. By combining microscopic molecular simulation methods with macroscopic slow-release performance analysis, the structure-activity relationship of the slow-release performance of the main slow-release agent and the competitive slow-release agent in the slow-release agent group in the porous slow-release material is elucidated. The diffusion behavior of the main slow-release agent in the slit pore model (porous slow-release material) is revealed by molecular simulation, and the preferred ratio between the main slow-release agent and the competitive slow-release agent in the porous slow-release material is determined to improve the slow-release effect, providing a new design idea for the design of porous slow-release materials and the optimization of slow-release performance.

[0034] Figure 1 An application scenario diagram of the molecular simulation method for analyzing the slow-release process of a slow-release agent according to an embodiment of the present application is shown.

[0035] As shown in Figure 1 According to the application scenario 100 of the embodiment, the first terminal device 101, the second terminal device 102, the third terminal device 103, the network 104, and the server 105 can be included. The network 104 is used as a medium to provide a communication link between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 can include various connection types, such as wired, wireless communication links, or optical fiber cables, etc.

[0036] A user can use the first terminal device 101, the second terminal device 102, and the third terminal device 103 to interact with the server 105 through the network 104 to receive or send messages, etc. Various communication client applications can be installed on the first terminal device 101, the second terminal device 102, and the third terminal device 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only as examples).

[0037] The first terminal device 101, the second terminal device 102 and the third terminal device 103 can be various electronic devices (or computing devices) with display screens and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers and desktop computers, and the like.

[0038] The server 105 can be a server providing various services, for example, a background management server supporting the operation of the user using the first terminal device 101, the second terminal device 102 and the third terminal device 103 to issue a molecular simulation request (only for example). The background management server can process the received molecular simulation request to obtain molecular simulation data, such as the competitive adsorption characteristic data, the competitive diffusion characteristic data and the sustained release analysis data of each of the plurality of sustained release agents, and feed back to the terminal device.

[0039] It should be noted that the molecular simulation method for analyzing the sustained release of the sustained release agent provided by the present application can be executed by the first terminal device 101, the second terminal device 102 or the third terminal device 103, or by other terminal devices different from the first terminal device 101, the second terminal device 102 or the third terminal device 103. Accordingly, the molecular simulation device for analyzing the sustained release of the sustained release agent provided by the present application can also be provided in the first terminal device 101, the second terminal device 102 or the third terminal device 103, or in other terminal devices different from the first terminal device 101, the second terminal device 102 or the third terminal device 103. Alternatively, the molecular simulation method for analyzing the sustained release of the sustained release agent provided by the present application can also be executed by the server 105. Accordingly, the molecular simulation device for analyzing the sustained release of the sustained release agent provided by the present application can also be provided in the server 105. The molecular simulation method for analyzing the sustained release of the sustained release agent provided by the present application can also be executed by a server or a server cluster different from the server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103 and / or the server 105. Accordingly, the molecular simulation device for analyzing the sustained release of the sustained release agent provided by the present application can also be provided in a server or a server cluster different from the server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103 and / or the server 105.

[0040] It should be understood that Figure 1 The number of terminal devices, networks and servers in the system is only an example. According to the needs of implementation, there can be any number of terminal devices, networks and servers.

[0041] Figure 2A flow chart of a molecular simulation method for analyzing the release of a slow-release agent in a slow-release process is shown.

[0042] As shown in Figure 2 The molecular simulation method for analyzing the release of a slow-release agent in a slow-release process includes steps S201-S203.

[0043] Step S201: The Monte Carlo method is used to simulate the adsorption process of each of a plurality of slow-release agent groups in a target slit pore model, to obtain competitive adsorption characteristic data of each of the plurality of slow-release agent groups, wherein the slow-release agent groups include a main slow-release agent and a competitive slow-release agent, the ratio of the main slow-release agent to the competitive slow-release agent is different in different slow-release agent groups, the target slit pore model is a slow-release material with a target pore size, the target pore size takes into account the adsorption and diffusion of the main slow-release agent and the competitive slow-release agent in the slow-release material, and the competitive adsorption characteristic data includes first adsorption characteristic data of the main slow-release agent and the competitive slow-release agent.

[0044] Step S202: The molecular dynamics method is used to simulate the diffusion process of each of the plurality of slow-release agent groups in the target slit pore model, to obtain competitive diffusion characteristic data of each of the plurality of slow-release agent groups, and the competitive diffusion characteristic data includes first diffusion characteristic data of the main slow-release agent and the competitive slow-release agent.

[0045] Step S203: Slow-release analysis data of the main slow-release agent and the competitive slow-release agent in the target slit pore model is obtained according to the competitive adsorption characteristic data and the competitive diffusion characteristic data of each of the plurality of slow-release agent groups.

[0046] In the embodiments of the present application, the adsorption process and the diffusion process of each of a plurality of slow-release agent groups in a target slit pore model (i.e., a slow-release material) are simulated by a molecular simulation method. The obtained competitive adsorption characteristic data is used to characterize the adsorption behavior of the slow-release agent groups in the slow-release material with a target pore size, and the obtained competitive diffusion characteristic data is used to characterize the diffusion behavior of the slow-release agent groups in the slow-release material with a target pore size. According to the competitive adsorption characteristic data and the competitive diffusion characteristic data, slow-release analysis data of the plurality of slow-release agent groups in the target slit pore model can be obtained, and the slow-release relationship between the pore size of the slow-release material and the slow-release agent groups and the relationship between each slow-release agent in the slow-release groups can be clarified according to the obtained slow-release analysis data, thereby laying a foundation for designing slow-release materials with higher slow-release performance and optimizing slow-release performance.

[0047] According to an embodiment of the present application, a three-dimensional model suitable for characterizing the microstructure of the slow-release material is stored in the molecular simulation software, and then the three-dimensional model is cut by a surface cutting technique to obtain a surface model, and a vacuum layer with different layer spacings is further established based on the surface model, i.e., a slit pore is constructed; and through structure optimization, a slit pore model with different pore sizes is obtained. In the structure optimization process, the Forcite module in the molecular simulation software is used, and the parameters are set as follows: the UFF force field is used to describe the van der Waals force, the QEq method is used to calculate the distribution charge, and the energy, interaction force, and translation distance threshold are set to 2×10 -5 kcal / mol, 1×10 -3 kcal / mol / Å, and 1×10 -5 Å, respectively. By controlling the size of the slit pore, slit pore models with different pore sizes (such as 5 angstroms (5 Å), 7 angstroms (7 Å), and 9 angstroms (9 Å)) can be obtained, wherein the pore sizes in the same slit pore model are the same.

[0048] According to an embodiment of the present application, the competitive adsorption characteristic data includes first adsorption characteristic data of the main slow-release agent and the competitive slow-release agent, wherein the first adsorption characteristic data includes at least one of a first adsorption isotherm, a first adsorption energy distribution, or a first adsorption density distribution.

[0049] The molecular simulation software is used to simulate the interaction behavior of the slow-release agent molecules (such as the main slow-release agent and the competitive slow-release agent) in the slow-release slit pore model (i.e., the slow-release material) by a Monte Carlo method, wherein the simulation parameters are set as follows: the UFF force field is used to describe the van der Waals force, the QEq method is used to calculate the distribution charge, the cutoff radius is set to 15.5 Å, the external gas pressure is set to a maximum of 1 bar, the temperature is set to 573 K, the number of Monte Carlo iteration steps is 1×10 6 steps, and the number of adsorption equilibrium steps is 1×10 5Each step calculation covers translation (i.e. Translate), rotation (i.e. Rotate), conformer (i.e. Conformer), regrowth (i.e. Regrow) and exchange (i.e. Exchange) behaviors. Specifically, the adsorption isotherm is used to characterize the relationship between the amount of adsorption and the pressure of the slit pore model (i.e. the slow-release material) at a constant temperature. The pore size distribution, pore volume and specific surface area, adsorption mechanism, stability and regeneration of the slow-release material can be determined by the adsorption isotherm. The adsorption energy density and adsorption energy distribution of the slow-release material are calculated by the method of fixed adsorption amount. The adsorption energy distribution is used to characterize the energy of the slow-release agent molecules in all possible positions in the slit pore model (slow-release material) and their interactions during the adsorption process, such as the interaction energy between slow-release agent molecules and the interaction energy between slow-release agent molecules and the pore of the slow-release material. The adsorption density distribution is used to characterize the spatial distribution of the slow-release agent molecules in the slit pore model. By quantifying the molecular packing density in different regions, the pore structure of the slow-release material, the filling behavior of the slow-release agent molecules, and the interaction between the adsorption sites and the surface of the slow-release material are determined, which lays a foundation for the subsequent functionalization design and structure optimization of the slow-release material.

[0050] According to an embodiment of the present application, the competitive diffusion characteristic data comprises first diffusion characteristic data of the main slow-release agent and the competitive slow-release agent respectively, wherein the first diffusion characteristic data comprises at least one of first root mean square displacement data, first radial distribution function data or first diffusion velocity field distribution data.

[0051] The Forcite module in the molecular simulation software is used to simulate the diffusion behavior of the sustained-release agent molecules in the slit pore model (i.e., the sustained-release material) based on the molecular dynamics method, wherein the parameters set include: NVT ensemble (regular ensemble, describing the fixed particle number (N), volume (V), and temperature (T)), a temperature of 573 K, a step of 1 fs, and a total time length of 5000 ps. Specifically, the mean square displacement (MSD) data are used to characterize the diffusion behavior of the sustained-release agent in the sustained-release material, the diffusion coefficient of the sustained-release agent molecules in the slit pore of the sustained-release material is quantified, the microstructure of the sustained-release material and the macroscopic diffusion transmission performance of the sustained-release agent molecules are determined, such as the diffusion coefficient of the sustained-release agent molecules, the influence of the pore structure of the sustained-release material on the diffusion of the sustained-release agent molecules, the interaction and adsorption behavior between the sustained-release agent molecules and the sustained-release material. The radial distribution function (RDF) is used to characterize the spatial arrangement and local structure of the sustained-release agent molecules in the slit pore of the sustained-release material, and the distance between the sustained-release agent molecules and the surface of the sustained-release material is quantified, so that the interaction between the sustained-release agent molecules and the surface of the sustained-release material, the pore structure characteristics of the sustained-release material, and the filling behavior of the sustained-release agent molecules can be obtained. The diffusion velocity field distribution data are used to characterize the transmission behavior of the sustained-release agent molecules in the slit pore of the sustained-release material, and the velocity of the sustained-release agent molecules in the slit pore of the sustained-release material is quantified, so that the diffusion path, the direction difference and the velocity difference of the sustained-release agent molecules during diffusion can be determined.

[0052] According to the embodiments of the present application, before step S201 is performed, the present application is used for the molecular simulation method for analyzing the sustained-release process of the sustained-release agent, further comprising: performing steps A1-A3.

[0053] Step A1: the Monte Carlo simulation method is used to simulate the adsorption process of the main sustained-release agent in each of the plurality of slit pore models, to obtain second adsorption characteristic data of each of the plurality of slit pore models, wherein the plurality of slit pore models have different pore diameters from each other; the second adsorption characteristic data includes at least one of a second adsorption isotherm, a second adsorption energy distribution, or a second adsorption density distribution.

[0054] In the embodiments of the present application, a plurality of slit pore models are constructed by using the molecular simulation software, and the plurality of slit pore models have different pore diameters from each other (such as 5 Å, 7 Å, 9 Å, etc., and the simulation pore diameter is not limited to the listed ones). Subsequently, the Monte Carlo method is used to simulate the adsorption process of the main sustained-release agent in each of the plurality of slit pore models, and the obtained second adsorption characteristic data can characterize the adsorption behavior of the main sustained-release agent molecules in the slit pore models with different pore diameters, and further determine the interaction relationship between the main sustained-release agent molecules and the slit pore channels of the slit pore models.

[0055] Step A2: simulate the diffusion process of the main sustained-release agent in each of the plurality of slit pore models by using molecular dynamics method to obtain second diffusion characteristic data of each of the plurality of slit pore models. The second diffusion characteristic data includes at least one of second root-mean-square displacement data, second radial distribution function data, or second diffusion velocity field distribution data.

[0056] In the embodiments of the present application, the obtained second diffusion characteristic data is used to characterize the diffusion velocity of the main sustained-release agent molecules in the slit pore model and the interaction relationship between the sustained-release agent molecules and the slit pore channel of the slit pore model.

[0057] Step A3: determining the target slit pore model from the plurality of slit pore models according to the second adsorption characteristic data and the second diffusion characteristic data of each of the plurality of slit pore models.

[0058] In the embodiments of the present application, by comprehensively considering the adsorption behavior and diffusion behavior of the main sustained-release agent in the slit pore model, a slit pore model with a moderate pore size, i.e., the target slit pore model, is determined, which is a sustained-release material with a target pore size, the size of which is between the thicknesses of single-layer and double-layer main sustained-release agent molecules, and which can take into account the adsorption and diffusion of the main sustained-release agent in the target slit pore model, and can also take into account the adsorption and diffusion of the main sustained-release agent and the competitive sustained-release agent in the target slit pore model.

[0059] It should be noted that the simulation process of the second adsorption characteristic data and the second diffusion characteristic data is the same as the simulation process of the first adsorption characteristic data and the first diffusion characteristic data, and "first" and "second" are only used to distinguish the simulation processes of the system containing only the main sustained-release agent and the sustained-release agent group (containing the competitive sustained-release agent and the main sustained-release agent) in the slit pore model.

[0060] According to the embodiments of the present application, in step A3, the target slit pore model is determined from the plurality of slit pore models according to the second adsorption characteristic data and the second diffusion characteristic data of each of the plurality of slit pore models, including steps A31-A33.

[0061] Step A31: determining at least one first target slit pore model from the plurality of slit pore models according to the second adsorption characteristic data of each of the plurality of slit pore models, wherein in the first target slit pore model, the probability of interaction between the primary sustained release agent molecules is greater than the probability of interaction between the primary sustained release agent molecules and the inner wall of the pore channel of the first target slit pore model. In other words, by simulating the adsorption process of the primary sustained release agent in each of the plurality of slit pore models by the Monte Carlo method, the second adsorption isotherm, the second adsorption energy distribution data, etc. of the primary sustained release agent molecules in different pore size slit pore models can be obtained, and by analyzing the second adsorption characteristic data, at least one first target slit pore model can be determined from the plurality of slit pore models. In the first target slit pore model, the adsorption amount of the primary sustained release agent molecules is moderate, and in addition to the interaction between the primary sustained release agent molecules and the pore channel, there is also interaction between the primary sustained release agent molecules in the pore channel of the sustained release material, and the probability of interaction between the primary sustained release agent molecules is higher, which is more conducive to the adsorption of the primary sustained release agent molecules.

[0062] Step A32: determining at least one second target slit pore model from the plurality of slit pore models according to the second diffusion characteristic data of each of the plurality of slit pore models, wherein in the second target slit pore model, the diffusion speed of the primary sustained release agent in the first direction is greater than the diffusion speed of the primary sustained release agent in the second direction, and the first direction and the second direction are opposite directions. In the present application, in addition to considering the adsorption behavior of the sustained release slit pore model, the diffusion behavior of the primary sustained release agent in the slit pore model also needs to be considered. By simulating the diffusion behavior of the primary sustained release agent molecules in the plurality of slit pore models by the molecular simulation method, the diffusion mode (such as the diffusion speed) of the primary sustained release agent molecules in different sustained release materials can be determined, so that the second target slit pore model can be determined.

[0063] Step A33: determining a target slit pore model according to at least one first target slit pore model and at least one second target slit pore model. In the present application, the adsorption behavior and diffusion behavior of the primary sustained release agent in the slit pore model are comprehensively considered, and the target slit pore model is determined from the first target slit pore model and the second target slit pore model. The target slit pore model can take into account the adsorption performance and diffusion performance of the primary sustained release agent molecules.

[0064] According to the embodiments of the present application, the molecular simulation method for analyzing the sustained release process of the sustained release agent also includes: simulating the electrostatic distribution of the primary sustained release agent in the target slit pore model to obtain electrostatic field distribution data, which is used to characterize the interaction relationship between the primary sustained release agent and the active site in the slit pore of the target slit pore model. Specifically, the Dmol3 module of the molecular simulation software is used to simulate the electrostatic distribution of the primary sustained release agent in the target slit pore model, and the electrostatic field distribution data is obtained. 3The module simulates electrostatic distribution of the main sustained-release agent in the target slit pore model to analyze electrostatic interaction between the main sustained-release agent and the inner surface of the slit pore of the target slit pore model, wherein simulation parameters include: combination of GGA / PBE functionals and DNP basis set, self-consistent field set to converge to 1x10 -6 kcal / mol, and maximum iteration number is limited to 500 times. Dispersion weak interaction is corrected by using the Grimme method, electron orbital spin is kept relaxed, and atomic orbitals are processed by using an all-electron method. GGA (Generalized Gradient Approximation) belongs to an exchange-related functional, which can more accurately describe the exchange and correlation between electrons; PBE (Perdew-Burke-Ernzerhof) is a specific functional form under the GGA framework, which balances the calculation efficiency and accuracy, and is one of the functionals in the density functional theory (DFT) calculation.

[0065] According to the embodiment of the present application, in step S203, the sustained-release analysis data of the main sustained-release agent and the competitive sustained-release agent in the target slit pore model includes: a target ratio between the main sustained-release agent and the competitive sustained-release agent; and / or a sustained-release process of the main sustained-release agent and the competitive sustained-release agent in the target slit pore model.

[0066] In the embodiment of the present application, by performing molecular simulation on the main sustained-release agent, a target slit pore model capable of considering adsorption and diffusion is determined, which can not only consider the adsorption and diffusion of the main sustained-release agent, but also consider the adsorption and diffusion of the competitive sustained-release agent. Through the molecular simulation method, by analyzing the second adsorption characteristic data and the second diffusion characteristic data, the sustained-release process of the main sustained-release agent molecules in the slit pore model is revealed, which is not a mechanism that monotonically depends on the pore size, the preferred pore size of the slit pore model can be determined, and a direction for the design of the sustained-release material is provided. Further, the sustained-release agent group obtained by mixing the main sustained-release agent and the competitive sustained-release agent in different proportions is applied to the target slit pore model, and through quantitative characterization, the interaction mechanism between the sustained-release agent group and the active sites on the inner surface of the slit pore of the target slit pore model (i.e. the sustained-release material), and the mechanism of the main sustained-release agent and the competitive sustained-release agent competing for adsorption, diffusion and sustained-release in the target slit pore model can be determined, and the addition amount of the main sustained-release agent and the competitive sustained-release agent can be determined, so as to optimize the sustained-release performance of the main sustained-release agent in the sustained-release material in the presence of the competitive sustained-release agent.

[0067] According to the embodiment of the present application, the simulation parameters of the Monte Carlo method and the molecular dynamics method include a simulation temperature, which is 573K, the same as the temperature when the cigarette is burned, which can better evaluate the sustained-release effect of the sustained-release agent molecules in the sustained-release material in the cigarette, and help to improve the taste of the cigarette and improve the user experience.

[0068] According to the embodiments of the present application, the slow-release material in the present application includes any one of diatomite, activated carbon, and zeolite, the pore size of the slow-release material is 5 Å, 7 Å, 9 Å, preferably 7 Å, which can take into account the synergistic effect of single-layer and double-layer molecular diffusion, and achieve the balance of adsorption and diffusion; the main slow-release agent is selected from glycerol; the competitive slow-release agent is selected from polyethylene glycol with a molecular weight of 150-200 g / mol, the molecular chain length of which matches the pore size of the slit pore model of diatomite, avoiding excessive blockage of the transmission channel. The addition amount ratio of the main slow-release agent and the competitive slow-release agent is 1:9-9:1, for example, glycerol:polyethylene glycol is 1:9, 3:7, 5:5.

[0069] The following takes diatomite (SiO2) to construct a slit pore model, glycerol (G) as the main slow-release agent, and / or polyethylene glycol trimer (polyethylene glycol, E3) as the competitive slow-release agent to simulate the adsorption and diffusion behavior in the slit pore model of diatomite, wherein the molecular weight of the polyethylene glycol is 200 g / mol, and the molecular chain length thereof matches the pore size of the slit pore model of diatomite, avoiding excessive blockage of the transmission channel. In the simulation process, the addition amount ratio of glycerol:polyethylene glycol in the slow-release agent group is 10:0-1:9 (such as 10:0, 9:1, 7:3, 5:5, 3:7, 1:9, etc.).

[0070] Figure 3 The following takes diatomite (SiO2) to construct a slit pore model, glycerol (G) as the main slow-release agent, and / or polyethylene glycol trimer (polyethylene glycol, E3) as the competitive slow-release agent to simulate the adsorption and diffusion behavior in the slit pore model of diatomite, wherein the molecular weight of the polyethylene glycol is 200 g / mol, and the molecular chain length thereof matches the pore size of the slit pore model of diatomite, avoiding excessive blockage of the transmission channel. In the simulation process, the addition amount ratio of glycerol:polyethylene glycol in the slow-release agent group is 10:0-1:9 (such as 10:0, 9:1, 7:3, 5:5, 3:7, 1:9, etc.).

[0071] As shown in Figure 3 The molecular simulation method for analyzing the slow-release process of glycerol in the slit pore model of diatomite includes steps S301-S307.

[0072] Step S301: based on a three-dimensional model of diatomite, a surface model is obtained by cutting the three-dimensional model through a surface cutting technique, and the surface model is optimized in structure to obtain a plurality of slit pore models of diatomite, wherein the plurality of slit pore models of diatomite have different pore sizes from each other.

[0073] Step S302: the adsorption behavior of glycerol molecules in the plurality of slit pore models of diatomite is simulated by a Monte Carlo method to obtain adsorption characteristic data of the plurality of slit pore models of diatomite respectively.

[0074] Step S303: the diffusion process of glycerol molecules in the plurality of slit pore models is simulated by a molecular dynamics method to obtain diffusion characteristic data of the plurality of slit pore models of diatomite respectively.

[0075] Step S304: according to the adsorption characteristic data and the diffusion characteristic data of the plurality of slit pore models of diatomite respectively, a target slit pore model of diatomite is determined from the plurality of slit pore models of diatomite, wherein the target slit pore model of diatomite has a target pore size.

[0076] Step S305: The Monte Carlo method is used to simulate the adsorption process of multiple slow-release agent groups in the target diatomaceous earth slit pore model, and competitive adsorption characteristic data of each slow-release agent group are obtained. The slow-release agent groups include glycerol and polyethylene glycol in different mixing ratios. The target diatomaceous earth slit pore model can take into account the adsorption and diffusion of the main slow-release agent and the competing slow-release agent in the diatomaceous earth. The competitive adsorption characteristic data include glycerol analysis and the adsorption characteristic data of polyethylene glycol.

[0077] Step S306: The diffusion process of multiple slow-release agent groups in the slit pore model of the target diatomaceous earth is simulated using molecular dynamics methods to obtain the competitive diffusion characteristic data of each of the multiple slow-release agent groups. The competitive diffusion characteristic data includes the diffusion characteristic data of glycerol and polyethylene glycol.

[0078] Step S307: Based on the competitive adsorption and diffusion characteristic data of each of the multiple sustained-release agent groups, obtain the sustained-release analysis data of glycerol and polyethylene glycol in the target diatomaceous earth slit pore model.

[0079] According to an embodiment of the present invention, in step S301, based on the SiO2 three-dimensional model provided by the molecular simulation software, a surface model is obtained by cutting using surface cutting technology. Then, based on the surface model, vacuum layers with different interlayer spacings are further established (i.e., slit pores are constructed), and structural optimization is performed to obtain multiple diatomaceous earth slit pore models with pore sizes of 5 Å, 7 Å, and 9 Å. During the structural optimization process, the Forcite module in the molecular simulation software is used, and the parameters are set as follows: using a UFF force field to describe van der Waals forces, calculating the partition charge using the QEq method, and setting the energy, interaction force, and translation distance thresholds to 2 × 10⁻⁶. -5 kcal / mol, 1×10 -3 kcal / mol / Å, 1×10 -5 Å.

[0080] For the simulated adsorption process of pure glycerol molecules, the adsorption isotherms (i.e., adsorption amount), adsorption energy distribution, and adsorption density distribution of glycerol molecules are simulated and calculated using diatomaceous earth slit pore models with different pore sizes. For the simulated diffusion process of pure glycerol molecules, the dynamic diffusion of glycerol molecules is mainly simulated and calculated using diatomaceous earth slit pore models with different pore sizes, such as root mean square displacement, radial distribution function, and diffusion velocity field distribution.

[0081] According to an embodiment of the present invention, in step S302, the Sorption module in molecular simulation software is used to simulate the interaction behavior of glycerol molecules in diatomaceous earth slit pore models with different pore sizes based on the Monte Carlo method. Specifically, the adsorption isotherm is calculated using an isothermal method, and the adsorption density distribution and adsorption energy distribution are calculated using a fixed adsorption amount method. The parameter settings during the adsorption process include: using a UFF force field to describe van der Waals forces, calculating the partition charge using the QEq method, setting the cutoff radius to 15.5 Å, setting the maximum external gas pressure to 1 bar, and setting the number of Monte Carlo iterations for adsorption equilibrium to 1 × 10⁻⁶ steps. 5 The number of steps used for statistical analysis is 1 × 10. 6 Each step involves calculations covering the translation, rotation, conformation, reconstruction, and substitution behaviors of molecules.

[0082] Figure 4 This is an adsorption isotherm diagram of pure glycerol molecules in diatomaceous earth slit pore models with different pore sizes in an embodiment of the present invention.

[0083] like Figure 4 As shown, the adsorption behavior of glycerol molecules in diatomaceous earth slit-pore models with different pore sizes (5Å, 7Å, and 9Å) is basically consistent. In all cases, an adsorption layer gradually forms on the surface of the diatomaceous earth crystal, and then, with increasing pressure, in-pore filling adsorption begins (corresponding to the turning point in the adsorption isotherm). The difference lies in the saturation adsorption capacity of the diatomaceous earth slit-pore models, which varies due to the different pore sizes and the resulting different internal pore spaces. However, the saturation adsorption capacity of the three different pore sizes is positively correlated with the pore size. Furthermore, the pressure required for in-pore filling adsorption also differs. For 7Å and 9Å pore sizes, in-pore filling adsorption occurs at pressures below 1 kPa, while for the 5Å pore size, a higher pressure (6 kPa) is required. This may be because the smaller slit-pore space is limited; when surface adsorption becomes saturated, the internal space is very cramped, requiring higher pressure to allow glycerol molecules to enter the pore and achieve filling behavior.

[0084] Figure 5 This is a diagram showing the adsorption energy distribution of pure glycerol molecules in diatomaceous earth slit pore models with different pore sizes in an embodiment of the present invention.

[0085] The adsorption energy distribution also corresponds to the adsorption behavior of the adsorption isotherm. For example... Figure 5As shown, the adsorption energy distribution represents the probability of glycerol molecules traversing all possible positions of the diatomite pores during the adsorption process and experiencing all interaction energies. As can be seen from the results, the energy distribution of glycerol molecules in the 7Å-9Å pore size is relatively close and the peak energy position is higher than that in the 5Å pore size, indicating that in the 7Å-9Å pore size, glycerol molecules not only interact with the inner wall of the diatomite slit pore, but also more likely interact with other glycerol molecules, which is more conducive to adsorption, while in the 5Å pore size, glycerol molecules mainly interact with the diatomite slit pore, and the interaction force between glycerol molecules is limited.

[0086] According to the embodiment of the present application, in step S303, the Forcite module in the molecular simulation software is used to simulate the diffusion behavior of glycerol molecules in the diatomite slit pore model with different pore sizes based on the molecular dynamics method, and the simulation parameter settings include: NVT ensemble, temperature 573K, step 1fs, and total time 5000ps.

[0087] Figure 6 Fig. 2 is a graph of the diffusion behavior of pure glycerol molecules in the diatomite slit pore model with different pore sizes according to the embodiment of the present application, wherein (a) is a mean square displacement graph, and (b) is a velocity field distribution graph of the pure glycerol molecules perpendicular to the direction of the diatomite slit pore with different pore sizes.

[0088] As Figure 6 can be seen from (a) of Fig. 3, from the perspective of kinetics, the 5Å pore size is the smallest among the three pore sizes (5Å, 7Å, 9Å) studied, and the glycerol molecules diffuse the slowest in the slit pore, i.e., the diffusion coefficient is the smallest. However, in the diatomite skeleton, the diffusion degree and the size of the slit pore do not always present a positive correlation, as Figure 6 can be seen from (b) of Fig. 3. Figure 6

[0089] As Figure 6 ​As shown in (b) in the figure, the glycerol molecules diffuse in opposite directions near the upper and lower surfaces of the slit pores of diatomite, that is, the velocity field has positive and negative values. In terms of the results, the diffusion speeds of the glycerol molecules in the 5 Å and 9 Å slit pores in the positive and negative directions are approximately equivalent. Specifically, for the 5 Å slit pore, the slit pore space is narrow and can only accommodate a single layer of glycerol molecules to diffuse, and the glycerol molecules can diffuse in both the positive and negative directions, so the probability of collision between the molecules is high and the diffusion speed is slow. For the 9 Å slit pore, the slit pore space is large and can accommodate two layers of glycerol molecules to freely diffuse, but unlike the 5 Å slit pore, a single glycerol molecule can only interact with the inner surface of the diatomite on one side, so that the 9 Å slit pore has insufficient driving force for glycerol diffusion and exhibits a slow diffusion speed. For the 7 Å slit pore, the slit pore size is between the thicknesses of a single layer and two layers of glycerol molecules, and from the velocity field distribution, the speed in the negative direction (0.8 Å / ps) is faster than that in the positive direction (0.2 Å / ps), and the speed difference is obvious, indicating that due to the limited space of the slit pore, the glycerol molecules diffusing in the negative direction can have a strong interaction with the glycerol molecules diffusing in the positive direction, change the diffusion direction and carry these molecules to diffuse in the negative direction, and finally make the glycerol molecules in the 7 Å slit pore have the fastest diffusion speed.

[0090] According to the embodiment of the present application, in step S304, therefore, the adsorption performance and diffusion performance of the pure glycerol molecules in the diatomite slit pore models with different pore sizes are comprehensively determined, and it is determined that the target (preferably) pore size of the diatomite slit pore model is 7 Å, the slit pore size is between the thicknesses of a single layer and two layers of glycerol molecules, the diffusion and adsorption of the glycerol molecules can be considered, and the presence of the glycerol molecules and other competitive sustained-release agent molecules can also be considered.

[0091] Furthermore, after determining that the diatomite slit pore model has a preferred pore size, the present application can also analyze the interaction between the glycerol molecules and the active sites of diatomite. Therefore, the present application uses the Dmol 3 module in the molecular simulation software to calculate the electrostatic field distribution of the glycerol molecules and the diatomite slit pore model to analyze the electrostatic interaction between the glycerol molecules and the inner surface of the diatomite slit pore, wherein the simulation calculation parameters include: the combination of GGA / PBE functional and DNP basis set, the self-consistent field is set to converge to 1x10 -6 kcal / mol, the maximum number of iterations is limited to 500 times. The Grimme method is used to correct the dispersion weak interaction, the electron orbital spin relaxation is maintained, and the atomic orbit is processed by the full electron processing method.

[0092] Figure 7 The electrostatic field distribution diagram of the pure glycerol molecules in the diatomite slit pore model with a pore size of 7 Å in the embodiment of the present application.

[0093] The main component of diatomite is silicon dioxide (SiO2), and the exposed sites in the inner surface are mainly oxygen (O) sites and silicon (Si) sites. As shown in Figure 7 From the electrostatic field distribution of the inner surface of the diatomite pore and the glycerol molecule, the oxygen sites mainly present a negative electric field, and the silicon sites relatively present a positive electric field. From the electrostatic field distribution of the glycerol molecule, the H in the -OH functional group has a relatively obvious positive electric field, in other words, the glycerol molecule can mainly interact with the oxygen sites in the inner pore of diatomite through the H in OH. Therefore, in the subsequent design of diatomite materials, the adsorption of glycerol molecules can be enhanced by increasing oxygen-containing groups, and the slow-release effect of diatomite on glycerol can be improved. In addition, through the electrostatic field distribution, a design direction is provided for the design and performance optimization of other porous slow-release materials.

[0094] In the glycerol single-component study, it was found that the 7 Å channel could have both glycerol adsorption capacity and diffusion performance, so the 7 Å channel was selected as the research object in the dual-component study. Polyethylene glycol trimer (E3, referred to as polyethylene glycol) was introduced as a competitive slow-release agent to simulate the competitive adsorption-diffusion behavior of the main slow-release agent glycerol and polyethylene glycol in the diatomite slit pore model with a pore size of 7 Å.

[0095] According to the embodiment of the present application, in step S305, the Sorption module in the molecular simulation software is used to simulate the competitive adsorption behavior of glycerol and polyethylene glycol in the diatomite slit pore model, and the set parameters include: using the UFF force field to describe the van der Waals force, using the QEq method to calculate the distribution charge, and setting the cutoff radius to 15.5 Å.

[0096] Figure 8 The adsorption density map of glycerol and polyethylene glycol with different mixing ratios in the diatomite slit pore model in the embodiment of the present application is shown in FIG. 5, wherein blue represents glycerol (G) and red represents polyethylene glycol (E3).

[0097] As shown in Figure 8 When polyethylene glycol is gradually mixed into glycerol (the ratio of G:E3 is 7:3), polyethylene glycol preferentially occupies the adsorption sites on the surface of SiO2, so that part of the glycerol molecules cannot fully contact the surface, that is, an adsorption competition effect is formed. In addition, the volume of the polyethylene glycol molecule is larger than that of the glycerol molecule, so the addition of the polyethylene glycol molecule will also cause a steric hindrance effect, to a certain extent, occupying the effective adsorption space in the slit pore. When the ratio of glycerol and polyethylene glycol reaches 5:5, the competition effect of the mixed polyethylene glycol and glycerol reaches the maximum, the added polyethylene glycol is quickly excluded from the diatomite slit pore, causing no polyethylene glycol in the pore at the adsorption equilibrium. When the mixed polyethylene glycol is further increased, the ratio exceeds 5:5 (such as the ratio of G:E3 is 3:7, 1:9), too much polyethylene glycol can be re-stabilized in the channel.

[0098] To further conduct quantitative research on thermodynamics, the above-mentioned... Figure 8 The adsorption energy distribution shown is as follows: Figure 9 As shown.

[0099] Figure 9 This is an energy distribution diagram showing the interaction between glycerol and polyethylene glycol in different mixing ratios on the surface of a diatomaceous earth slit pore model in an embodiment of the present invention.

[0100] like Figure 9 As shown, under different mixing ratios of glycerol and polyethylene glycol (E3), the interaction energy between E3 and the SiO2 surface is always slightly greater than that of glycerol molecules. When the mixing ratio of glycerol (G) and E3 reaches 7:3, the interaction energy distribution curve of E3 shows two significant peaks, indicating that E3 may be affected by two interactions: one is the interaction between E3 and the SiO2 surface, and the other is the strong hydrogen bonding between E3 molecules. The hydrogen bonding between E3 molecules helps to increase the strength of the intermolecular linkages, making the E3 competitive release agent more firmly anchored on the SiO2 surface, thereby achieving the slow release of glycerol.

[0101] According to an embodiment of the present invention, in step S306, the competitive diffusion behavior of glycerol and polyethylene glycol in the diatomaceous earth slit pore model is simulated using the Forcite module in molecular simulation software. The parameters set include: NVT ensemble, temperature 573K, step size 1fs, and total duration 5000ps.

[0102] Figure 10 This is a diagram showing the kinetic diffusion curves of glycerol and polyethylene glycol in different mixing ratios in a diatomaceous earth slit pore model according to embodiments of the present invention. Figure 11 for Figure 10 A horizontal comparison chart.

[0103] like Figure 10 As shown in the simulation results, the MSD value of pure glycerol molecules (10 equivalent molecules) is around 1500 Å within the studied time range. 2 Around 800 Å, when polyethylene glycol (E3) is gradually mixed into 10 glycerol molecules to a ratio of 7:3, the MSD value of the glycerol molecules is gradually reduced to 800 Å. 2 The polydiethanol molecules are highly polar and contain abundant OH groups, which readily form strong hydrogen bonds with the SiO2 surface and preferentially adsorb onto the SiO2 surface and within the pores. This occupies a limited number of adsorption sites, thus reducing the diffusion rate of glycerol molecules. This indicates that the incorporated polydiethanol can effectively achieve a sustained-release effect on glycerol.

[0104] likeFigures 10-11 Further transverse comparison of the diffusion of glycerol under different mixing ratios, it is found that when the polyethylene glycol is further increased (such as G:E3=1:9), the larger volume of polyethylene glycol molecules may block the original transmission channel of glycerol molecules to a greater extent, forcing glycerol molecules to change the diffusion path (into the secondary diffusion channel smaller than the polyethylene glycol molecule), thereby promoting the diffusion of glycerol molecules, and the MSD is increased to 2500 Å 2 The above causes the diffusion speed of glycerol molecules to increase, reducing the slow-release effect of glycerol in the diatomite slit pore model.

[0105] According to the embodiments of the present application, in step S307, the preferred amount of addition of the main slow-release agent and the competitive slow-release agent in the slow-release agent group is determined according to the competitive adsorption characteristic data and the competitive diffusion characteristic data of the slow-release agent group, so as to improve the slow-release effect of the main slow-release agent. For example, through the analysis of the above Figures 3-11 The present application clarifies the structure-activity relationship between the pore size of diatomite and the slow-release performance of glycerol, and reveals the mechanism that the diffusion speed of glycerol molecules in the slit pore is not monotonously dependent on the pore size. Based on the adsorption energy distribution data and the root mean square displacement data, the present application studies by regulating the addition ratio of polyethylene glycol, and characterizes the interaction mechanism between glycerol and polyethylene glycol and the inner surface of the diatomite slit pore as hydrogen bond. Meanwhile, the competitive adsorption mechanism between polyethylene glycol and the inner surface of the diatomite slit pore and glycerol molecules is clarified, so as to optimize the addition amount of the diatomite slit pore size, glycerol and polyethylene glycol. When polyethylene glycol is used as the competitive slow-release agent, the molecular weight of polyethylene glycol and the addition amount of polyethylene glycol and glycerol should be controlled. For example, when the glycerol and polyethylene glycol are 7:3 in the present application, the diffusion MSD value of glycerol is reduced by 46% by using the competitive adsorption of glycerol and polyethylene glycol to occupy the oxygen sites on the inner surface of the diatomite slit pore and form an intermolecular hydrogen bond network, and the space steric hindrance effect of polyethylene glycol can effectively improve the slow-release effect of glycerol. However, more addition amount of polyethylene glycol trimer may promote the diffusion of glycerol due to the synergistic effect of competitive adsorption and space steric hindrance, and therefore the amount of polyethylene glycol needs to be paid attention to in use. According to the embodiments of the present application,

[0106] According to the embodiments of the present application, the present application further provides a slow-release method of a slow-release agent, which comprises: determining the target pore size and the target ratio based on the above-mentioned molecular simulation method for analyzing the slow-release agent in the slow-release process; using the slow-release material with the target pore size as an adsorption carrier; mixing the main slow-release agent and the competitive slow-release agent according to the target ratio, and then adding them into the adsorption carrier for adsorption and diffusion; and testing the slow-release rate of the main slow-release agent in the adsorption carrier.

[0107] For example, diatomite with a pore size of 7 Å is selected as the carrier material; polyethylene glycol (molecular weight 150 g / mol) is added in a ratio of 7:3 of glycerol and polyethylene glycol in the bulk phase, and then mixed and added to the 7 Å diatomite carrier material for adsorption and diffusion; the release rate of diatomite for glycerol is tested at 573 K, and the MSD value is controlled within 1500 Å 2 .

[0108] Figure 12 A structural block diagram of a molecular simulation device for analyzing the release of a release agent in a release process is shown in the embodiments of the present application.

[0109] As Figure 12 shown, the molecular simulation device 1200 for analyzing the release of a release agent in a release process includes an adsorption simulation module 1210, a diffusion simulation module 1220, and a data analysis module 1230.

[0110] The adsorption simulation module 1210 includes a first adsorption simulation module adapted to simulate the adsorption process of each of a plurality of release agent groups in a target slit pore model using a Monte Carlo method, to obtain competitive adsorption characteristic data of each of the plurality of release agent groups, wherein the release agent groups include a main release agent and a competitive release agent, the proportion of the main release agent to the competitive release agent is different in different release agent groups, the target slit pore model is a release material with a target pore size, the target pore size takes into account the adsorption and diffusion of the main release agent and the competitive release agent in the release material, and the competitive adsorption characteristic data includes first adsorption characteristic data of the main release agent and the competitive release agent. Further, the first adsorption simulation module is provided with the above-mentioned Sorption module.

[0111] The diffusion simulation module 1220 includes a first diffusion simulation module adapted to simulate the diffusion process of each of a plurality of release agent groups in a target slit pore model using a molecular dynamics method, to obtain competitive diffusion characteristic data of each of the plurality of release agent groups, and the competitive diffusion characteristic data includes first diffusion characteristic data of the main release agent and the competitive release agent. Further, the first diffusion simulation module is provided with a Forcite module.

[0112] The data analysis module 1230 includes a first data analysis submodule adapted to obtain release analysis data of the main release agent and the competitive release agent in the target slit pore model according to the competitive adsorption characteristic data and the competitive diffusion characteristic data of each of the plurality of release agent groups.

[0113] According to an embodiment of the present application, the sorption simulation module 1210 further comprises a second sorption simulation module, which is adapted to simulate the sorption process of the main slow-release agent in each of the plurality of slit pore models by using a Monte Carlo simulation method, to obtain second sorption characteristic data of each of the plurality of slit pore models, wherein the plurality of slit pore models have different pore diameters.

[0114] According to an embodiment of the present application, the diffusion simulation module 1220 further comprises a second diffusion simulation module, which is adapted to simulate the diffusion process of the main slow-release agent in each of the plurality of slit pore models by using a molecular dynamics method, to obtain second diffusion characteristic data of each of the plurality of slit pore models.

[0115] According to an embodiment of the present application, the data analysis module 1230 further comprises a second data analysis sub-module, which is adapted to determine a target slit pore model from the plurality of slit pore models according to the second sorption characteristic data and the second diffusion characteristic data of each of the plurality of slit pore models.

[0116] According to an embodiment of the present application, the second data analysis sub-module comprises a first determination unit, a second determination unit and a third determination unit.

[0117] The first determination unit is adapted to determine at least one first target slit pore model from the plurality of slit pore models according to the second sorption characteristic data of each of the plurality of slit pore models, wherein in the first target slit pore model, the probability of interaction between the main slow-release agent molecules is greater than the probability of interaction between the main slow-release agent molecules and the inner wall of the pore channel of the first target slit pore model.

[0118] The second determination unit is adapted to determine at least one second target slit pore model from the plurality of slit pore models according to the second diffusion characteristic data of each of the plurality of slit pore models, wherein in the second target slit pore model, the diffusion speed of the main slow-release agent in a first direction is greater than the diffusion speed of the main slow-release agent in a second direction, and the first direction and the second direction are opposite directions.

[0119] The third determination unit determines the target slit pore model according to the at least one first target slit pore model and the at least one second target slit pore model.

[0120] According to embodiments of the present application, any of the adsorption simulation module 1210, the diffusion simulation module 1220, and the data analysis module 1230 can be combined in one module, or any of them can be split into multiple modules. Alternatively, at least part of the function of one or more of these modules can be combined with at least part of the function of the other modules, and implemented in one module. According to embodiments of the present application, at least one of the adsorption simulation module 1210, the diffusion simulation module 1220, and the data analysis module 1230 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on chip, a system on board, a system on package, an application specific integrated circuit (ASIC), or any other reasonable way of integrating or packaging a circuit, etc., or implemented in software, hardware, and firmware in any one of them or in a proper combination of any of them. Alternatively, at least one of the adsorption simulation module 1210, the diffusion simulation module 1220, and the data analysis module 1230 can be at least partially implemented as a computer program module that, when executed, can perform the corresponding function.

[0121] Figure 13 A block diagram of a computing device suitable for implementing a method for analyzing a molecular simulation of a sustained release agent in a sustained release process according to embodiments of the present application is shown.

[0122] As shown in Figure 13 The computing device 1300 according to embodiments of the present application includes a processor 1301 that can perform various appropriate actions and processes according to programs stored in a read only memory (ROM) 1302 or loaded from a storage section 1308 into a random access memory (RAM) 1303. The processor 1301 can include, for example, a general purpose microprocessor (e.g., a CPU), an instruction set processor, and / or a related chipset and / or a dedicated microprocessor (e.g., an application specific integrated circuit (ASIC)), etc. The processor 1301 can also include an on-board memory for cache use. The processor 1301 can include a single processing unit or multiple processing units for performing different actions of the method processes according to embodiments of the present application.

[0123] In the RAM 1303, various programs and data required for the operation of the computing device 1300 are stored. The processor 1301, the ROM 1302, and the RAM 1303 are connected to each other via the bus 1304. The processor 1301 performs various operations of the method flow according to the embodiments of the present application by executing the programs in the ROM 1302 and / or the RAM 1303. It is to be noted that the programs described above can also be stored in one or more memories other than the ROM 1302 and the RAM 1303. The processor 1301 can also perform various operations of the method flow according to the embodiments of the present application by executing the programs stored in the one or more memories described above.

[0124] According to the embodiments of the present application, the computing device 1300 can further include an input / output (I / O) interface 1305, which is also connected to the bus 1304. The computing device 1300 can further include one or more of the following components connected to the input / output (I / O) interface 1305: an input portion 1306 including a keyboard, a mouse, etc.; an output portion 1307 including a display such as a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 1308 including a hard disk, etc.; and a communication portion 1309 including a network interface card such as a LAN card, a modem, etc. The communication portion 1309 performs communication processing via a network such as the Internet. A drive 1310 is also connected to the input / output (I / O) interface 1305 as necessary. A removable recording medium 1311 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, and the like is attached to the drive 1310 as necessary, so that a computer program read out therefrom is installed in the storage portion 1308 as necessary.

[0125] The present application also provides a computer readable storage medium, which can be included in the device / apparatus / system described in the above embodiments; or can exist separately without being assembled into the device / apparatus / system. The above computer readable storage medium carries one or more programs, which, when executed, implement the molecular simulation method according to the embodiments of the present application.

[0126] According to an embodiment of the present application, the computer readable storage medium can be a non-transitory computer readable storage medium, for example, can include, but is not limited to, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device. For example, according to an embodiment of the present application, the computer readable storage medium can include one or more of the memory described above as ROM 1302 and / or RAM 1303, and / or one or more memory other than the ROM 1302 and the RAM 1303.

[0127] Embodiments of the present application also include a computer program product, which includes a computer program containing program codes for executing the method shown in the flow chart. When the computer program product is run in a computer system, the program codes are used to make the computer system implement the molecular simulation method provided by the embodiments of the present application.

[0128] The above functions defined in the system / device of the embodiments of the present application are performed when the computer program is executed by the processor 1301. According to an embodiment of the present application, the system, device, module, unit, etc. described above can be implemented by computer program modules.

[0129] In one embodiment, the computer program can rely on tangible storage media such as optical storage media, magnetic storage media, etc. In another embodiment, the computer program can also be transmitted, distributed, and downloaded in the form of signals on a network medium, and be downloaded and installed through the communication part 1309, and / or installed from the detachable medium 1311. The program codes contained in the computer program can be transmitted by any suitable network medium, including but not limited to wireless, wired, etc., or any suitable combination of the foregoing.

[0130] In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 1309, and / or installed from the detachable medium 1311. When the computer program is executed by the processor 1301, the above functions defined in the system of the embodiments of the present application are performed. According to an embodiment of the present application, the system, device, apparatus, module, unit, etc. described above can be implemented by computer program modules.

[0131] According to an embodiment of the present application, program code for implementing the computer programs provided by embodiments of the present application can be written in any combination of one or more programming languages, and can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. The programming languages include, but are not limited to, Java, C++, python, "C" language, or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any kind of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, connected to the Internet through an Internet service provider).

[0132] The flow diagrams and the block diagrams in the drawings are illustrations of possible architectures, functions, and operations for systems, methods, and computer program products according to various embodiments of the present application. In this regard, each block in the flow diagrams or block diagrams can represent a module, a segment, or a portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the blocks can occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and / or flow diagrams, and combinations thereof, can be implemented by special purpose hardware-based systems that perform the specified functions or operations, or combinations of special purpose hardware and computer instructions.

[0133] The above-described specific embodiments are merely intended to further describe the purpose, technical solutions and beneficial effects of the present application, and should be understood that the above-described specific embodiments are merely specific embodiments of the present application and are not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A molecular simulation method for analyzing sustained-release agents during the sustained-release process, characterized in that, include: The Monte Carlo method was used to simulate the adsorption process of multiple sustained-release agent groups in a target slit pore model, obtaining competitive adsorption characteristic data for each group. Each sustained-release agent group includes a main sustained-release agent and a competing sustained-release agent, with different ratios of the main and competing agents in different groups. The target slit pore model is a sustained-release material with a target pore size, which accommodates both the adsorption and diffusion of the main and competing agents within the material. The competitive adsorption characteristic data includes the first adsorption characteristic data for each of the main and competing agents. The diffusion process of each of the multiple sustained-release agent groups in the target slit pore model was simulated using molecular dynamics methods to obtain competitive diffusion characteristic data of each of the multiple sustained-release agent groups. The competitive diffusion characteristic data includes the first diffusion characteristic data of each of the main sustained-release agent and the competing sustained-release agent. Based on the competitive adsorption and diffusion characteristics of the multiple sustained-release agent groups, sustained-release analysis data of the main sustained-release agent and the competing sustained-release agents in the target slit pore model are obtained.

2. The molecular simulation method according to claim 1, characterized in that, Also includes: The Monte Carlo simulation method was used to simulate the adsorption process of the main sustained-release agent in each of the multiple slit pore models, and the second adsorption characteristic data of each of the multiple slit pore models were obtained, wherein the multiple slit pore models have different pore sizes. The diffusion process of the main sustained-release agent in each of the multiple slit-hole models was simulated using the molecular dynamics method to obtain the second diffusion characteristic data of each of the multiple slit-hole models. The target slit hole model is determined from the plurality of slit hole models based on the second adsorption characteristic data and the second diffusion characteristic data of each of the plurality of slit hole models.

3. The molecular simulation method according to claim 2, characterized in that, The step of determining the target slit hole model from the plurality of slit hole models based on the second adsorption characteristic data and the second diffusion characteristic data of each of the plurality of slit hole models includes: Based on the second adsorption characteristic data of each of the plurality of slit pore models, at least one first target slit pore model is determined from the plurality of slit pore models, wherein in the first target slit pore model, the probability of interaction between the main sustained-release molecules is greater than the probability of interaction between the main sustained-release molecules and the inner wall of the pore of the first target slit pore model. Based on the second diffusion characteristic data of each of the plurality of slit hole models, at least one second target slit hole model is determined from the plurality of slit hole models, wherein in the second target slit hole model, the diffusion rate of the main sustained-release agent in the first direction is greater than the diffusion rate of the main sustained-release agent in the second direction, and the first direction and the second direction are opposite directions; The target slit hole model is determined based on the at least one first target slit hole model and the at least one second target slit hole model.

4. The molecular simulation method according to claim 3, characterized in that, Also includes: The electrostatic distribution of the main sustained-release agent in the target slit hole model is simulated to obtain electrostatic field distribution data, wherein the electrostatic distribution data is used to characterize the interaction relationship between the main sustained-release agent and the active sites in the slit hole of the target slit hole model.

5. The molecular simulation method according to any one of claims 1-4, characterized in that, The sustained-release analysis data of the primary sustained-release agent and the competing sustained-release agent in the target slit pore model include: The target ratio between the primary sustained-release agent and the competing sustained-release agent; and / or The release process of the primary and competing sustained-release agents in the target slit-hole model.

6. The molecular simulation method according to any one of claims 1-3, characterized in that, The first adsorption characteristic data includes at least one of: a first adsorption isotherm, a first adsorption energy distribution, or a first adsorption density distribution; and / or The first diffusion characteristic data includes at least one of the following: first root mean square displacement data, first radial distribution function data, or first diffusion velocity field distribution data.

7. The molecular simulation method according to claim 2 or 3, characterized in that, The second adsorption characteristic data includes at least one of a second adsorption isotherm, a second adsorption energy distribution, or a second adsorption density distribution; and / or The second diffusion characteristic data includes at least one of the following: second root mean square displacement data, second radial distribution function data, or second diffusion velocity field distribution data.

8. The molecular simulation method according to claim 1, characterized in that, The simulation parameters for the Monte Carlo method and the molecular dynamics method include a simulation temperature of 573 K.

9. The molecular simulation method according to claim 1, characterized in that, The slow-release material includes any one of diatomaceous earth, activated carbon, and zeolite; The primary sustained-release agent is selected from glycerol; The competitive sustained-release agent is selected from polyethylene glycol.

10. A method for sustained release of a sustained-release agent, characterized in that, include: Based on the target pore size and target ratio determined by the molecular simulation method for analyzing the sustained-release agent during the sustained-release process as described in any one of claims 1-9; A sustained-release material with the target pore size is used as the adsorption carrier; The main sustained-release agent and the competing sustained-release agent are mixed according to the target ratio and then added to the adsorption carrier for adsorption and diffusion. The release rate of the main sustained-release agent in the adsorbent carrier was tested.

Images