Method for enhancing dispersity of graphite aqueous solution by using anionic composite surfactant based on molecular dynamics simulation

Abstract

The invention relates to a method for enhancing the dispersibility of a graphite aqueous solution by using an anionic composite surfactant based on molecular dynamics simulation, which comprises the following steps: establishing an initial model, introducing graphite unit cells, and constructing water molecules and anionic surfactant molecules; performing energy minimization operation on the initial model, and performing geometric optimization on the initial model; establishing an intermediate model, wherein the intermediate model comprises a graphite substrate model, an anionic composite surfactant overall model and a water molecule overall model; combining the intermediate models to form a graphite / anionic composite surfactant / water interface model; carrying out geometric optimization on the graphite / anionic composite surfactant / water interface model; selecting a proper interatomic interaction potential function, and setting proper simulation parameters and steps so as to perform molecular dynamics simulation on the final interface model; and obtaining dynamic information of the interface model. The method has the beneficial effects that the operation is simple, the cost is low, the precision is high, and the optimization of the formula of the composite surfactant is facilitated.

Description

Technical Field

[0001] The invention relates to the field of colloid interface science and technology, and in particular to a method for enhancing the dispersibility of graphite solution by using anionic composite surfactant based on molecular dynamics simulation. Background Art

[0002] Graphite has a wide range of applications in the fields of coatings, chemicals, and new energy due to its excellent performance. However, graphite is insoluble in water, which limits its storage and application in aqueous media. Therefore, it is crucial to improve the dispersibility of graphite solutions. Surfactants can greatly improve the dispersibility and stability of graphite solutions, but traditional single surfactants often have problems with short-lasting dispersion effects and low efficiency. In order to obtain better dispersion effects, surfactants of different properties can be compounded to utilize their synergistic effects to effectively reduce surface tension, improve dispersibility and stability. Among them, anionic surfactants show better stability and significant synergistic effects in promoting graphite dispersion, and they provide an economical and environmentally friendly solution for graphite dispersion at a lower cost and with greater environmental friendliness. In addition, anionic composite surfactants exhibit stronger polar interaction ability than monoanionic surfactants, which makes the adsorption ability of anionic composite surfactants on the graphite surface stronger, and can more effectively reduce the van der Waals force between graphite sheets, thereby improving the dispersion stability. However, the commonly used experimental methods have the disadvantages of being time-consuming and labor-intensive, complicated to operate, and unable to monitor the dispersion effect in real time. Therefore, it is particularly important to use computational simulation methods to analyze the dispersibility of composite surfactants in graphite solutions.

[0003] Molecular dynamics simulation technology has made significant progress in recent years and has shown its unique value and broad application prospects in many scientific fields. This technology is based on molecular models, uses classical potential energy functions to describe the interactions between molecules, and solves Newton's equations of motion to track the motion trajectories of molecules. Through this method, we can capture the dynamic information of the composite surfactant evolving over time in the process of enhancing the dispersibility of graphite solution, thereby gaining a deep understanding of the microscopic dynamic changes of graphite during the dispersion process.

[0004] CN116312853A discloses a method for evaluating a surfactant compound system based on molecular dynamics simulation, which provides theoretical guidance for the research of surfactant compound systems.

[0005] Nevertheless, there are currently no reports on the dispersibility of anionic composite surfactants in graphite solutions based on molecular dynamics simulation, which indicates that this field still needs further exploration and research. Summary of the invention

[0006] The technical problem to be solved by the present invention is to provide a method for enhancing the dispersibility of graphite in an aqueous solution based on molecular dynamics simulation, so as to solve the problems of traditional experimental methods in dispersing graphite, such as it being difficult to accurately determine data parameters with a single surfactant, high experimental costs, long time periods, and difficult data analysis.

[0007] The technical solution of the present invention to solve the above technical problems is as follows:

[0008] A method for enhancing the dispersibility of graphite in an aqueous solution based on molecular dynamics simulation of an anionic composite surfactant includes the following steps:

[0009] Step1. Import a graphite unit cell in Materials Studio software and construct water molecules and two or more anionic surfactant molecules to establish an initial model;

[0010] Step2. First perform an energy minimization operation on the initial model, and then perform geometric optimization on it;

[0011] Step3. Respectively establish intermediate models, including: a graphite substrate model, an overall model of an anionic composite surfactant, and an overall model of water molecules;

[0012] Step4. Combine the graphite substrate model, the overall model of the anionic composite surfactant, and the overall model of water molecules to form a graphite / anionic composite surfactant / water interface model;

[0013] Step5. Perform geometric optimization on the graphite / anionic composite surfactant / water interface model;

[0014] Step6. Select an appropriate interatomic interaction potential function and set appropriate simulation parameters and steps to perform molecular dynamics simulation on the final interface model;

[0015] Step7. Obtain the kinetic information of the interface model.

[0016] On the basis of the above technical solution, the present invention can also be improved as follows.

[0017] Further, Step2 is specifically as follows:

[0018] Step2-1: Select the Energy task in the Forcite module to perform an energy minimization operation on the initial model and use the COMPASSⅡ force field. Among them, the charges are automatically set and allocated by the force field, the accuracy is set to Medium, the Ewald summation method is used for electrostatic force calculation, the Atom-based summation method is used for van der Waals force calculation, and the Smart algorithm is selected for optimization;

[0019] Step 2-2: Select the Geometry optimization task in the Forcite module to perform geometric optimization on the initial model. Set the calculation accuracy to Medium. For electrostatic force calculation, use the Ewald summation method, and for van der Waals force calculation, use the Atom-based summation method. Use the COMPASSⅡ force field, and the charges are automatically assigned by the force field.

[0020] Furthermore, set the maximum number of iterations ≥ 1000.

[0021] Further, Step 3 is specifically as follows:

[0022] Step 3-1: First, cut along different crystal planes of the graphite unit cell. Subsequently, use the Supercell function in Build to obtain a larger supercell model by expanding the cell. The size of the model is set according to the Medium accuracy and is greater than 2 times the Rcut value. Finally, set the thickness of the vacuum layer around the model to to ensure that atoms do not interact with the model boundary during the simulation, and obtain the graphite substrate model;

[0023] Step 3-2: Combine multiple anionic surfactant molecules, with the number ≥ 4, to obtain the overall model of the anionic composite surfactant, and the size of the overall model of the anionic composite surfactant is the same as that of the graphite substrate model;

[0024] Step 3-3: Select the Construction task in the Amorphous Cell module to combine single water molecules into multiple intermediate models of water molecules. Use the COMPASSⅡ force field, set the calculation accuracy to Medium, use the Ewald summation method for electrostatic force calculation, and use the Atom-based summation method for van der Waals force calculation. The number of water molecules ≥ 300, and set the density range of the aqueous solution to 0.1 g / cm 3 ~0.5 g / cm 3 to obtain the overall model of water molecules.

[0025] Further, Step 4 is specifically as follows: Combine the graphite substrate model, the overall model of the anionic composite surfactant, and the overall model of water molecules into a graphite / anionic composite surfactant / water interface model through the Build layer tool. The thickness of the vacuum layer of the graphite / anionic composite surfactant / water interface model is set to

[0026] Further, Step 5 specifically includes: Selecting the Geometry optimization task in the Forcite module to perform geometric optimization on the graphite / anionic composite surfactant / water interface model, setting the calculation accuracy to Medium, using the Ewald summation method for electrostatic force calculation, the Atom-based summation method for van der Waals force calculation, using the COMPASSⅡ force field, and automatically setting and distributing charges by the force field.

[0027] Furthermore, set the maximum number of iterations ≥ 1000.

[0028] Further, Step 6 specifically includes: Selecting the Dynamic task in the Forcite module to perform isothermal and isobaric ensemble simulation calculations on the graphite / anionic composite surfactant / water interface model, using the COMPASSⅡ force field, with a simulation time ≥ 100 ps, using the Nose temperature control method to maintain the simulation temperature, and the simulation temperature ≥ 298 K.

[0029] Further, the kinetic information in Step 7 includes: key calculation results such as the equilibrium configuration of the adsorption system, radial distribution function, interaction energy, hydrogen bonds, radial distribution function, and concentration distribution of each component along the Z-axis.

[0030] Further, the anionic surfactant in Step 1 is two or more of sodium dodecylbenzenesulfonate, disodium methylenedinaphthalenesulfonate, sodium dodecyl sulfate, α-olefin sulfonate, sodium dodecyl polyoxyethylene ether sulfate, alkyl sulfonate, sodium stearate, sodium lauroyl sarcosinate, and sodium lignosulfonate.

[0031] The beneficial effects of the present invention are:

[0032] 1) The present invention can accurately construct a graphite / anionic composite surfactant / water interface model at the molecular scale, and calculate the details of the adsorption process by simulating the interaction process of the three through molecular dynamics, so as to accurately, quickly, and effectively obtain the best surfactant type and dosage;

[0033] 2) The present invention can overcome the disadvantages of the conventional macroscopic experiments, such as the cumbersome and complex process, large errors in the obtained results, and great influence of human factors. That is, the method of the present invention has the advantages of simple operation, low cost, and high precision. It can not only provide an efficient theoretical tool for the research on the dispersibility of graphite, but also help to optimize the formulation of the composite surfactant, thereby improving the dispersion stability of the graphite aqueous solution. It shows great potential in the development of new high-performance materials and energy conservation and material reduction, provides a new strategy for exploring the preparation of highly dispersed and stable graphite dispersions, and provides a theoretical basis for the dispersion of graphite in aqueous solutions;

[0034] 3) The method of optimizing the formulation and usage conditions of anionic composite surfactants based on molecular dynamics simulation is conducive to precisely regulating the molecular structure and concentration of surfactants, predicting their adsorption behavior on the graphite surface, and evaluating their influence on the dispersibility of graphite. In addition, this method helps reduce the number of experiments and material waste, accelerate the development process of new materials, and thus promote the innovative applications of graphite-based materials in fields such as coatings, energy storage, and composite materials. Description of the Drawings

[0035] Figure 1 It is a flow chart of the method for enhancing the dispersibility of graphite aqueous solution by anionic composite surfactants based on molecular dynamics simulation in the present invention;

[0036] Figure 2 They are the initial model, intermediate model, and final model of Example 1;

[0037] Figure 3 They are the relative concentration distributions of graphite, surfactant, and water along the Z-axis in the graphite / anionic composite surfactant / water system before and after adsorption in Comparative Example 1, Comparative Example 2, and Example 1: (a) Sodium dodecylbenzenesulfonate (SDBS); (b) Sodium lignosulfonate (SL); (c) Sodium dodecylbenzenesulfonate + Sodium lignosulfonate; (d) Summary of the peak difference in relative concentration;

[0038] Figure 4 They are for Example 1, Comparative Example 1, and Comparative Example 2 in the graphite / surfactant / water model within 100 ps: (a) Adsorption energy of surfactant and water; (b) Interface formation energy;

[0039] Figure 5 It is the Zeta potential diagram of the graphite dispersion prepared according to the mass fraction ratios of surfactant, graphite, and water in Example 1, Comparative Example 1, and Comparative Example 2. Detailed Embodiments

[0040] The principles and features of the present invention are described below in conjunction with the accompanying drawings. The examples given are only for explaining the present invention and are not intended to limit the scope of the present invention.

[0041] Example 1

[0042] As Figures 1 to 5 shown, the method for enhancing the dispersibility of graphite aqueous solution by anionic composite surfactants based on molecular dynamics simulation includes the following steps:

[0043] Step1: Import a graphite unit cell in the Materials Studio software, and construct sodium dodecylbenzenesulfonate molecules, sodium lignosulfonate molecules, and water molecules to establish an initial model;

[0044] Step 2: Select the Energy task in the Forcite module to perform energy minimization on the initial model, and use the COMPASS II force field. Among them, the charges are automatically assigned by the force field. Set the accuracy to Medium. The Ewald summation method is used for electrostatic force calculation, and the Atom-based summation method is used for van der Waals force calculation. Select the Smart algorithm for optimization;

[0045] Select the Geometry optimization task in the Forcite module to perform geometric optimization on the initial model. Set the calculation accuracy to Medium. The Ewald summation method is used for electrostatic force calculation, and the Atom-based summation method is used for van der Waals force calculation. Use the COMPASS II force field. The charges are automatically assigned by the force field, and set the maximum number of iterations to 1000;

[0046] Step 3: Establish intermediate models respectively, including: graphite substrate model, sodium dodecylbenzenesulfonate + sodium lignosulfonate (anionic composite surfactant) overall model, and water molecule overall model;

[0047] Step 3-1: First, along the (2-10) plane section of the graphite unit cell. Subsequently, use the Supercell function in Build to expand the cell to obtain 1200 carbon atoms. The model size is set according to the Medium accuracy settings, all greater than 2 times Rcult, with the length, width, and height being Finally, set the thickness of the vacuum layer around the model to to ensure that atoms do not interact with the model boundary during the simulation, and obtain the graphite substrate model;

[0048] Step 3-2: Combine 4 sodium dodecylbenzenesulfonate molecules and 4 sodium lignosulfonate molecules to obtain the overall model of sodium dodecylbenzenesulfonate + sodium lignosulfonate molecules, and the size of the overall model of sodium dodecylbenzenesulfonate + sodium lignosulfonate molecules is the same as that of the graphite substrate model;

[0049] Step 3-3: Select the Construction task in the Amorphous Cell module to combine single water molecules into multiple water molecule intermediate models. Use the COMPASS II force field. Set the calculation accuracy to Medium. The Ewald summation method is used for electrostatic force calculation, and the Atom-based summation method is used for van der Waals force calculation. The number of water molecules is 1000. Set the density range of the aqueous solution to 0.1 g / cm 3 to obtain the overall water molecule model;

[0050] Step 4: Combine the graphite substrate model, the sodium dodecylbenzenesulfonate + sodium lignosulfonate molecular overall model, and the water molecular overall model through the Build layer tool to form a graphite / sodium dodecylbenzenesulfonate + sodium lignosulfonate / water interface model, and set the thickness of the model vacuum layer to

[0051] Step 5: Select the Geometry optimization task in the Forcite module to perform geometric optimization on the graphite / sodium dodecylbenzenesulfonate + sodium lignosulfonate / water interface model. Set the calculation accuracy to Medium, use the Ewald summation method for electrostatic force calculation, the Atom-based summation method for van der Waals force calculation, use the COMPASSⅡ force field, the charges are automatically assigned by the force field, and set the maximum number of iterations to 1000;

[0052] Step 6: Select the Dynamic task in the Forcite module to perform isothermal and isobaric ensemble (NVT) simulation calculations on the graphite / sodium dodecylbenzenesulfonate + sodium lignosulfonate / water interface model. Use the COMPASSⅡ force field, the simulation time is 1000 ps, the time step is 1 fs, use the Nose temperature control method to maintain the simulation temperature, and the simulation temperature is 298 K;

[0053] Step 7: Obtain the key calculation results of the equilibrium configuration, radial distribution function, interaction energy, hydrogen bonds, radial distribution function, and concentration distribution of each component along the Z-axis of the adsorption system of the graphite / sodium dodecylbenzenesulfonate + sodium lignosulfonate / water interface model at different times.

[0054] Example 2

[0055] A method for enhancing the dispersibility of graphite aqueous solution based on molecular dynamics simulation, which includes the following steps:

[0056] Step 1: Import a graphite unit cell in the Materials Studio software, and construct sodium dodecylbenzenesulfonate molecules, sodium lignosulfonate molecules, and water molecules to establish an initial model;

[0057] Step 2: Select the Energy task in the Forcite module to perform energy minimization on the initial model, and use the COMPASSⅡ force field. Among them, the charges are automatically assigned by the force field, set the accuracy to Medium, use the Ewald summation method for electrostatic force calculation, the Atom-based summation method for van der Waals force calculation, and select the Smart algorithm for optimization;

[0058] Select the Geometry optimization task in the Forcite module to perform geometric optimization on the initial model. Set the calculation accuracy to Medium, use the Ewald summation method for electrostatic force calculation, the Atom-based summation method for van der Waals force calculation, use the COMPASSⅡ force field, automatically assign charges by the force field, and set the maximum number of iterations to 2000;

[0059] Step3: Establish intermediate models respectively, including: graphite substrate model, sodium dodecylbenzenesulfonate + sodium lignosulfonate (anionic composite surfactant) overall model, and water molecule overall model;

[0060] Step3-1: First, cut along the (001) plane of the graphite unit cell. Subsequently, use the Supercell function in Build to expand the cell to obtain 1584 carbon atoms. The model size is set according to the Medium accuracy setting, all greater than 2 times Rcult, with the length, width, and height being respectively Finally, set the thickness of the vacuum layer around the model to to ensure that atoms do not interact with the model boundary during the simulation, and obtain the graphite substrate model;

[0061] Step3-2: Combine 4 sodium dodecylbenzenesulfonate molecules and 4 sodium lignosulfonate molecules to obtain the overall model of sodium dodecylbenzenesulfonate + sodium lignosulfonate molecules, and the size of the overall model of sodium dodecylbenzenesulfonate + sodium lignosulfonate molecules is the same as that of the graphite substrate model;

[0062] Step3-3: Select the Construction task in the Amorphous Cell module to combine single water molecules into multiple intermediate models of water molecules. Use the COMPASSⅡ force field, set the calculation accuracy to Medium, use the Ewald summation method for electrostatic force calculation, the Atom-based summation method for van der Waals force calculation, the number of water molecules is 300, and set the density range of the aqueous solution to 0.2g / cm 3 to obtain the overall model of water molecules;

[0063] Step4: Combine the graphite substrate model, the overall model of sodium dodecylbenzenesulfonate + sodium lignosulfonate molecules, and the overall model of water molecules through the Build layer tool to form a graphite / sodium dodecylbenzenesulfonate + sodium lignosulfonate / water interface model, and set the thickness of the model vacuum layer to

[0064] Step 5: Select the Geometry optimization task in the Forcite module to perform geometric optimization on the graphite / sodium dodecylbenzenesulfonate + sodium lignosulfonate / water interface model. Set the calculation accuracy to Medium, use the Ewald summation method for electrostatic calculations, the Atom-based summation method for van der Waals force calculations, use the COMPASS II force field, and let the charges be automatically assigned by the force field. Also, set the maximum number of iterations to 2000;

[0065] Step 6: Select the Dynamic task in the Forcite module to perform isothermal-isobaric ensemble (NVT) simulation calculations on the graphite / sodium dodecylbenzenesulfonate + sodium lignosulfonate / water interface model. Use the COMPASS II force field, with a simulation time of 2000 ps and a time step of 1 fs. Adopt the Nose temperature control method to maintain the simulation temperature at 313 K;

[0066] Step 7: Obtain the key calculation results of the equilibrium configuration, radial distribution function, interaction energy, hydrogen bonds, radial distribution function, and concentration distribution of each component along the Z-axis of the adsorption system of the graphite / sodium dodecylbenzenesulfonate + sodium lignosulfonate / water interface model at different times.

[0067] Example 3

[0068] A method for enhancing the dispersion of graphite in an aqueous solution using an anionic composite surfactant based on molecular dynamics simulation, which includes the following steps:

[0069] Step 1: Import a graphite unit cell in the Materials Studio software and construct sodium dodecylbenzenesulfonate molecules, sodium lignosulfonate molecules, and water molecules to establish an initial model;

[0070] Step 2: Select the Energy task in the Forcite module to perform energy minimization on the initial model and use the COMPASS II force field. Among them, the charges are automatically assigned by the force field. Set the accuracy to Medium, use the Ewald summation method for electrostatic calculations, the Atom-based summation method for van der Waals force calculations, and select the Smart algorithm for optimization;

[0071] Select the Geometry optimization task in the Forcite module to perform geometric optimization on the initial model. Set the calculation accuracy to Medium, use the Ewald summation method for electrostatic calculations, the Atom-based summation method for van der Waals force calculations, use the COMPASS II force field, and let the charges be automatically assigned by the force field. Also, set the maximum number of iterations to 1500;

[0072] Step 3: Establish intermediate models respectively, including: a graphite substrate model, an overall model of sodium dodecylbenzenesulfonate + sodium lignosulfonate (anionic composite surfactant), and an overall model of water molecules;

[0073] Step 3-1: First, cut along the (110) plane section of the graphite unit cell. Subsequently, use the Supercell function in Build to expand the cell to obtain 1056 carbon atoms. The model size is set according to the Medium precision setting, all greater than 2 times Rcult, with the length, width, and height being Set, all greater than 2 times Rcult, with the length, width, and height being Finally, set the thickness of the vacuum layer around the model to to ensure that atoms do not interact with the model boundary during the simulation, obtaining the graphite substrate model;

[0074] Step 3-2: Combine 4 sodium dodecylbenzenesulfonate molecules and 4 sodium lignosulfonate molecules to obtain an overall model of sodium dodecylbenzenesulfonate + sodium lignosulfonate molecules, and the size of the overall model of sodium dodecylbenzenesulfonate + sodium lignosulfonate molecules is the same as that of the graphite substrate model;

[0075] Step 3-3: Select the Construction task in the Amorphous Cell module to combine single water molecules into an intermediate model of multiple water molecules. Adopt the COMPASSⅡ force field, set the calculation precision to Medium, use the Ewald summation method for electrostatic force calculation, use the Atom-based summation method for van der Waals force calculation, the number of water molecules is 600, and set the density range of the aqueous solution to 0.5 g / cm 3 to obtain the overall model of water molecules;

[0076] Step 4: Combine the graphite substrate model, the overall model of sodium dodecylbenzenesulfonate + sodium lignosulfonate molecules, and the overall model of water molecules through the Build layer tool to form a graphite / sodium dodecylbenzenesulfonate + sodium lignosulfonate / water interface model, and set the thickness of the model vacuum layer to

[0077] Step 5: Select the Geometry optimization task in the Forcite module to perform geometric optimization operations on the graphite / sodium dodecylbenzenesulfonate + sodium lignosulfonate / water interface model. Set the calculation precision to Medium, use the Ewald summation method for electrostatic force calculation, use the Atom-based summation method for van der Waals force calculation, use the COMPASSⅡ force field, the charge is automatically assigned by the force field, and set the maximum number of iterations to 1500;

[0078] Step 6: Select the Dynamic task in the Forcite module to perform isothermal-isobaric ensemble (NVT) simulation calculations on the graphite / sodium dodecylbenzenesulfonate + sodium lignosulfonate / water interface model. Use the COMPASS II force field, with a simulation time of 1500 ps and a time step of 1 fs. Adopt the Nose temperature control method to maintain the simulation temperature at 298 K.

[0079] Step 7: Obtain the key calculation results of the equilibrium configuration, radial distribution function, interaction energy, hydrogen bonds, radial distribution function, and concentration distribution of each component along the Z-axis of the adsorption system of the graphite / sodium dodecylbenzenesulfonate + sodium lignosulfonate / water interface model at different times.

[0080] Comparative Example 1

[0081] As Figure 3 、 Figure 4 、 Figure 5 shown, a method for enhancing the dispersion of graphite in an aqueous solution by a single anionic surfactant based on molecular dynamics simulation includes the following steps:

[0082] Step 1: Import a graphite unit cell in the Materials Studio software and construct sodium dodecylbenzenesulfonate molecules and water molecules to establish an initial model.

[0083] Step 2: Select the Energy task in the Forcite module to perform energy minimization on the initial model and use the COMPASS II force field. Among them, the charges are automatically set and distributed by the force field, the setting accuracy is Medium, the Ewald summation method is used for electrostatic force calculation, the Atom-based summation method is used for van der Waals force calculation, and the Smart algorithm is selected for optimization.

[0084] Select the Geometry optimization task in the Forcite module to perform geometric optimization on the initial model. Set the calculation accuracy to Medium, use the Ewald summation method for electrostatic force calculation, the Atom-based summation method for van der Waals force calculation, use the COMPASS II force field, the charges are automatically set and distributed by the force field, and set the maximum number of iterations to 1000.

[0085] Step 3: Establish intermediate models respectively, including: a graphite substrate model, an overall model of sodium dodecylbenzenesulfonate, and an overall model of water molecules.

[0086] Step 3-1: First, along the (2-10) plane section of the graphite unit cell, and then use the Supercell function in Build to expand the cell to obtain 1200 carbon atoms. The model size is based on the accuracy of Medium. Set, all greater than 2 times Rcult, with length, width, and height being Finally, set the thickness of the vacuum layer around the model to to ensure that atoms do not interact with the model boundary during the simulation, obtaining a graphite substrate model;

[0087] Step3-2: Combine 4 sodium dodecylbenzenesulfonate molecules to obtain an overall model of sodium dodecylbenzenesulfonate, and the size of the overall model of sodium dodecylbenzenesulfonate is the same as that of the graphite substrate model;

[0088] Step3-3: Select the Construction task in the Amorphous Cell module to combine single water molecules into an intermediate model of multiple water molecules. Use the COMPASSⅡ force field, set the calculation accuracy to Medium, use the Ewald summation method for electrostatic force calculation, use the Atom-based summation method for van der Waals force calculation, the number of water molecules is 1000, and set the density range of the aqueous solution to 0.1g / cm 3 , to obtain an overall model of water molecules;

[0089] Step4: Combine the graphite substrate model, the overall model of sodium dodecylbenzenesulfonate molecules, and the overall model of water molecules through the Build layer tool to form a graphite / sodium dodecylbenzenesulfonate / water interface model, and set the thickness of the model vacuum layer to

[0090] Step5: Select the Geometry optimization task in the Forcite module to perform geometric optimization on the graphite / sodium dodecylbenzenesulfonate / water interface model. Set the calculation accuracy to Medium, use the Ewald summation method for electrostatic force calculation, use the Atom-based summation method for van der Waals force calculation, use the COMPASSⅡ force field, the charge is automatically assigned by the force field, and set the maximum number of iterations to 1000;

[0091] Step6: Select the Dynamic task in the Forcite module to perform isothermal-isobaric ensemble (NVT) simulation calculations on the graphite / sodium dodecylbenzenesulfonate / water interface model. Use the COMPASSⅡ force field, the simulation time is 1000ps, the time step is 1fs, use the Nose temperature control method to maintain the simulation temperature, and the simulation temperature is 298K;

[0092] Step7: Obtain key calculation results such as the equilibrium configuration, radial distribution function, interaction energy, hydrogen bonds, radial distribution function, and concentration distribution of each component along the Z-axis of the adsorption system of the graphite / sodium dodecylbenzenesulfonate / water interface model at different times.

[0093] Comparative Example 2

[0094] As Figure 3 、 Figure 4 、 Figure 5 shown, a method for enhancing the dispersion of graphite in an aqueous solution by a monoanionic surfactant based on molecular dynamics simulation includes the following steps:

[0095] Step1: Import a graphite unit cell in Materials Studio software, and construct sodium lignosulfonate molecules and water molecules to establish an initial model;

[0096] Step2: Select the Energy task in the Forcite module to perform energy minimization on the initial model, and use the COMPASSⅡ force field. Among them, the charges are automatically assigned by the force field, the precision is set to Medium, the Ewald summation method is used for electrostatic force calculation, the Atom-based summation method is used for van der Waals force calculation, and the Smart algorithm is selected for optimization;

[0097] Select the Geometry optimization task in the Forcite module to perform geometric optimization on the initial model, set the calculation precision to Medium, use the Ewald summation method for electrostatic force calculation, the Atom-based summation method for van der Waals force calculation, use the COMPASSⅡ force field, the charges are automatically assigned by the force field, and set the maximum number of iterations to 1000;

[0098] Step3: Establish intermediate models respectively, including: a graphite substrate model, an overall sodium lignosulfonate model, and an overall water molecule model;

[0099] Step3-1: First, along the (2-10) plane section of the graphite unit cell, and then, use the Supercell function in Build to expand the cell to obtain 1200 carbon atoms. The model size is set according to the precision Medium settings, all greater than 2 times Rcult, and the length, width, and height are respectively Finally, set the thickness of the vacuum layer around the model to to ensure that atoms do not interact with the model boundary during the simulation, and obtain a graphite substrate model;

[0100] Step3-2: Combine 4 sodium dodecylbenzenesulfonate molecules to obtain an overall sodium lignosulfonate model, and the size of the overall sodium lignosulfonate model is the same as that of the graphite substrate model;

[0101] Step3-3: Select the Construction task in the Amorphous Cell module to combine single water molecules into an intermediate model of multiple water molecules. Use the COMPASSⅡ force field, set the calculation accuracy to Medium, use the Ewald summation method for electrostatic calculations, use the Atom-based summation method for van der Waals force calculations, set the number of water molecules to 1000, and set the density range of the aqueous solution to 0.1g / cm 3 , to obtain the overall model of water molecules;

[0102] Step4: Combine the graphite substrate model, the overall model of sodium lignosulfonate, and the overall model of water molecules through the Build layer tool to form a graphite / sodium lignosulfonate / water interface model, and set the thickness of the model vacuum layer to

[0103] Step5: Select the Geometry optimization task in the Forcite module to perform geometric optimization operations on the graphite / sodium lignosulfonate / water interface model. Set the calculation accuracy to Medium, use the Ewald summation method for electrostatic calculations, use the Atom-based summation method for van der Waals force calculations, use the COMPASSⅡ force field, and the charges are automatically assigned by the force field, and set the maximum number of iterations to 1000;

[0104] Step6: Select the Dynamic task in the Forcite module to perform isothermal and isobaric ensemble (NVT) simulation calculations on the graphite / sodium lignosulfonate / water interface model. Use the COMPASSⅡ force field, the simulation time is 1000 ps, the time step is 1 fs, use the Nose temperature control method to maintain the simulation temperature, and the simulation temperature is 298 K;

[0105] Step7: Obtain the key calculation results of the equilibrium configuration, radial distribution function, interaction energy, hydrogen bonds, radial distribution function, and concentration distribution of each component along the Z-axis of the graphite / sodium lignosulfonate / water interface model at different times.

[0106] It can be seen from Figure 3 that the simulation shows that the concentrations of graphite and water molecules decrease after adsorption, while the surfactant concentration increases, indicating that the surfactant promotes the adsorption of water and graphite, forming a more compact structure. In addition, the concentration difference of the surfactant of sodium dodecylbenzenesulfonate + sodium lignosulfonate along the Z-axis before and after adsorption is 4.019, which is much higher than 0.143 of single sodium dodecylbenzenesulfonate and 0.157 of single sodium lignosulfonate, indicating that anionic surfactants are significantly effective in improving the dispersibility of graphite, far better than single surfactants.

[0107] It can be seen from Figure 4It can be seen that the average adsorption energies of surfactants sodium dodecylbenzenesulfonate, sodium lignosulfonate, and sodium dodecylbenzenesulfonate + sodium lignosulfonate with water are -340.07 KJ / mol, -340.65 KJ / mol, and -382.55 KJ / mol respectively, while the corresponding average interfacial formation energies are -3141.08 KJ / mol, -4688.95 KJ / mol, and -4792.22 KJ / mol respectively. This result shows that in the graphite / sodium dodecylbenzenesulfonate + sodium lignosulfonate / water system, the anionic composite surfactant exhibits the strongest adsorption effect and the highest interfacial formation energy. The synergistic effect of the two not only enhances the dispersion ability of graphite but also improves the stability of the system.

[0108] It can be seen from Figure 5 that the Zeta potentials of surfactants sodium dodecylbenzenesulfonate, sodium lignosulfonate, and sodium dodecylbenzenesulfonate + sodium lignosulfonate in the aqueous solution of graphite are -37.1 mV, -34.2 mV, and -39.8 mV respectively, indicating that the anionic surfactant has a good synergistic dispersion effect in the actual dispersion process and can effectively improve the dispersion of graphite in the aqueous solution compared with a single surfactant.

[0109] In the cases shown in Examples 1, 2, and 3 of this embodiment, only the combination of two anionic surfactants is exemplified, but in the actual simulation process, the combination of other two or more anionic surfactants is not excluded. The anionic surfactant can be selected from any combination of two or more of sodium dodecylbenzenesulfonate, sodium methylene bisnaphthalenesulfonate, sodium dodecyl sulfate, α-olefin sulfonate, sodium dodecyl polyoxyethylene ether sulfate, alkyl sulfonate, sodium stearate, sodium lauroyl sarcosinate, and sodium lignosulfonate as the research object.

[0110] For the embodiments of the present invention, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for enhancing the dispersibility of graphite in an aqueous solution by an anionic composite surfactant based on molecular dynamics simulation, characterized in that, It includes the following steps: Step 1: Import a graphite unit cell in Materials Studio software, and construct water molecules and two or more anionic surfactant molecules to establish an initial model; Step 2: First perform an energy minimization operation on the initial model, and then perform geometric optimization on it; Step 3: Respectively establish intermediate models, including: a graphite substrate model, an overall model of anionic composite surfactant, and an overall model of water molecules; Step 4: Combine the graphite substrate model, the overall model of anionic composite surfactant, and the overall model of water molecules to form a graphite / composite surfactant / water interface model; Step 5: Perform geometric optimization on the graphite / anionic composite surfactant / water interface model; Step 6: Select an appropriate interatomic interaction potential function, and set appropriate simulation parameters and steps to perform molecular dynamics simulation on the final interface model; Step 7: Obtain the kinetic information of the interface model.

2. The method for enhancing the dispersibility of graphite aqueous solution by anionic composite surfactant based on molecular dynamics simulation according to claim 1, characterized in that, Specifically, Step 2 is as follows: Step 2-1: Select the Energy task in the Forcite module to perform an energy minimization operation on the initial model, and use the COMPASSⅡ force field. Among them, the charges are automatically set and assigned by the force field. Set the accuracy to Medium, use the Ewald summation method for electrostatic force calculation, use the Atom-based summation method for van der Waals force calculation, and select the Smart algorithm for optimization; Step 2-2: Select the Geometry optimization task in the Forcite module to perform a geometric optimization operation on the initial model. Set the calculation accuracy to Medium, use the Ewald summation method for electrostatic force calculation, use the Atom-based summation method for van der Waals force calculation, use the COMPASSⅡ force field, and the charges are automatically set and assigned by the force field.

3. The method for enhancing the dispersibility of graphite aqueous solution by anionic composite surfactant based on molecular dynamics simulation according to claim 1 or 2, characterized in that, Set the maximum number of iterations ≥ 1000.

4. The method for enhancing the dispersibility of graphite aqueous solution by anionic composite surfactant based on molecular dynamics simulation according to claim 1, characterized in that Specifically, Step 3 is as follows: Step3-1: First, cut along different crystal planes of the graphite unit cell. Subsequently, use the Supercell function in Build to obtain a larger supercell model by expanding the cell. The size of the model is set according to the Medium precision and is greater than 2 times the Rcut value. Finally, set the thickness of the vacuum layer around the model to to ensure that atoms do not interact with the model boundary during the simulation, and obtain the graphite substrate model; Step 3-2: Combine multiple anionic surfactant molecules, with the number ≥ 4, to obtain an overall model of anionic composite surfactant, and the size of the overall model of anionic composite surfactant is the same as that of the graphite substrate model; Step 3-3: Select the Construction task in the Amorphous Cell module to combine single water molecules into an intermediate model of multiple water molecules. Use the COMPASS II force field, set the calculation accuracy to Medium, use the Ewald summation method for electrostatic force calculation, use the Atom-based summation method for van der Waals force calculation, the number of water molecules ≥ 300, and set the density range of the aqueous solution to 0.1 g / cm 3 ~0.5 g / cm 3 , so as to obtain an overall model of water molecules.

5. The method for enhancing the dispersibility of graphite in an aqueous solution by an anionic composite surfactant based on molecular dynamics simulation according to claim 1, wherein Step 4 is specifically as follows: The graphite substrate model, the overall model of anionic composite surfactant, and the overall model of water molecules are combined into a graphite / anionic composite surfactant / water interface model through the Build layer tool, and the vacuum layer thickness of the graphite / anionic composite surfactant / water interface model is set to 6. The method for enhancing the dispersibility of graphite aqueous solution by anionic composite surfactant based on molecular dynamics simulation according to claim 1, wherein Specifically, Step 5 is as follows: Select the Geometry optimization task in the Forcite module to perform a geometric optimization operation on the graphite / anionic composite surfactant / water interface model. Set the calculation accuracy to Medium, use the Ewald summation method for electrostatic force calculation, use the Atom-based summation method for van der Waals force calculation, use the COMPASSⅡ force field, and the charges are automatically set and assigned by the force field.

7. The method for enhancing the dispersibility of graphite in an aqueous solution by an anionic composite surfactant based on molecular dynamics simulation according to claim 1 or 6, characterized in that, Set the maximum number of iterations ≥ 1000.

8. The method for enhancing the dispersion of graphite in an aqueous solution by an anionic composite surfactant based on molecular dynamics simulation according to claim 1, characterized in that Step 6 specifically involves: Selecting the Dynamic task in the Forcite module to perform isothermal-isobaric ensemble simulation calculations on the graphite / anionic surfactant / water interface model. Using the COMPASS II force field, the simulation time is ≥100 ps. The Nose temperature control method is used to maintain the simulation temperature, and the simulation temperature is ≥298 K.

9. The method for enhancing the dispersibility of graphite in an aqueous solution by an anionic composite surfactant based on molecular dynamics simulation according to claim 1, characterized in that, The kinetic information in Step 7 includes: Key calculation results such as the equilibrium configuration of the adsorption system, radial distribution function, interaction energy, hydrogen bonds, radial distribution function, and the concentration distribution of each component along the Z-axis.

10. The method for enhancing the dispersibility of graphite aqueous solution by anionic composite surfactant based on molecular dynamics simulation according to any one of claims 1 to 9, characterized in that, The anionic surfactants in Step 1 are two or more of sodium dodecylbenzenesulfonate, disodium methylenedinaphthalenesulfonate, sodium dodecyl sulfate, α-olefin sulfonate, sodium dodecyl polyoxyethylene ether sulfate, alkyl sulfonate, sodium stearate, sodium lauroyl sarcosinate, and sodium lignosulfonate.

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