Method for simulating and calculating homopolymerized rubber binary blending system phase diagram by using computer
By constructing a coarse-grained blending model and optimizing the force field parameters, the problem of large calculation errors in the phase diagram of the binary rubber blending system in the existing technology is solved, and more accurate phase diagram drawing is achieved, which is applicable to rubber products such as tires.
Patent Information
- Application Number
- CN202511600880.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-04
- Publication Date
- 2026-03-17
AI Technical Summary
Existing computer simulation methods neglect structural parameters such as crosslinking density and chain entanglement of rubber molecular chains when drawing phase diagrams for homopolymer rubber binary blends. This results in large calculation errors for phase separation temperature and phase region boundaries, and the force field parameters are not optimized for rubber properties, leading to insufficient accuracy.
A blending model was constructed using a repeating unit and coarse-grained site mapping strategy. Crosslinking density and molecular chain entanglement were introduced, and force field parameters were optimized. Phase behavior characteristic parameters were monitored through molecular dynamics simulation, and a phase diagram was drawn.
It improves the calculation accuracy of phase separation temperature and phase region boundary, reduces experimental costs and cycle time, provides more accurate force field parameters and more comprehensive phase diagrams, and is applicable to the field of rubber products such as tires.
Smart Images
Figure CN121687271A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of computational simulation and phase diagram prediction technology of polymer materials, specifically a method for using computer simulation to calculate the phase diagram of a homopolymer rubber binary blend system. Background Technology
[0002] Homopolymer rubber binary blend system refers to a mixed system formed by physical blending of two different homopolymer rubbers as core components. Homopolymer rubber binary blend system is widely used in the field of rubber products such as tires and seals because the mechanical properties and aging resistance of materials can be synergistically optimized by adjusting the ratio and molecular structure of the two rubbers.
[0003] In the field of tire products, phase diagrams of homopolymer rubber binary blends are commonly obtained using computer simulation and experimental methods. Experimental methods primarily rely on differential scanning calorimetry, small-angle X-ray scattering, and optical microscopy to determine the phase states of blends with different ratios at various temperatures. However, this method suffers from significant drawbacks, including long experimental cycles and high material costs. Existing computer simulation methods are mostly based on the Flory-Huggins theoretical model, calculating the interaction parameters of the two rubbers and predicting the phase diagram through thermodynamic derivation. However, these methods have key shortcomings: firstly, they neglect the influence of core structural parameters such as the crosslinking density and chain entanglement of rubber molecules on phase behavior, leading to large calculation errors in phase separation temperature and phase boundary conditions; secondly, the force field parameters often use general polymer force fields without optimization for the flexible segments and side group characteristics of rubber molecules, resulting in insufficient accuracy in calculating intermolecular interactions. Therefore, improvements to this method are urgently needed. Summary of the Invention
[0004] The purpose of this invention is to provide a method for calculating the phase diagram of a homopolymer rubber binary blend system using computer simulation, so as to solve the problems mentioned in the background art.
[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for calculating the phase diagram of a homopolymer rubber binary blend system using computer simulation, the specific steps of which are as follows: Step 1: Obtain the basic parameters of the homopolymer rubber binary blend system The two homopolymer rubber components of the blend system are identified, denoted as rubber A and rubber B. The molecular structure parameters, aggregate state structure parameters and thermodynamic parameters are obtained through experimental determination or molecular structure analysis. Step 2: Based on the molecular structure parameters obtained in Step 1, the molecular chains of rubber A and rubber B are coarsened using a repeating unit and coarse-grained site mapping strategy. According to the crosslinking density, crosslinking points are introduced between the molecular chains through a random crosslinking algorithm to construct a coarse-grained blending model. Representative local regions in the coarse-grained model are selected, and the coarse-grained sites are restored to the full-atom structure through the inverse mapping algorithm to obtain the full-atom blend model. At the same time, the energy minimization algorithm is used to optimize the structure of the full-atom model and eliminate unreasonable spatial steric hindrance between atoms. Step 3: Optimize the force field parameters of the rubber blend system 3.1 Preliminary selection of force field: Based on the general polymer force field COMPASS II, the all-atom blending model constructed in step two is imported; 3.2 Force field parameter correction: The torsional potential energy of the C-C bonds in the rubber molecular chain was corrected by combining quantum chemical calculation results; the van der Waals interaction parameters between the rubber side groups and the main chain were corrected by fitting density data at different temperatures through molecular dynamics simulations and adjusting the Lennard-Jones potential energy parameters so that the deviation between the simulated density and the experimental density was ≤3%. 3.3 Verification of the effectiveness of the force field: Molecular dynamics simulations were performed on a single rubber component using the modified force field to calculate its glass transition temperature Tg. If the deviation between the simulated Tg and the experimental Tg is ≤2℃, the force field parameters are qualified; otherwise, step 3.2 is repeated for iterative correction. Step 4: Import the coarse-grained blending model constructed in Step 2 into molecular simulation software, and use the NPT ensemble to perform molecular dynamics simulations of the coarse-grained model at multiple temperature gradients; during the simulation, record the following phase behavior characteristic parameters according to the set monitoring frequency: Density fluctuation parameter (Δρ): The phase separation trend is characterized by calculating the density standard deviation of a local region of the system. When Δρ ≥ 0.02 g / cm³, phase separation is determined to have occurred. Scattering intensity parameter (I(q)): The scattering intensity distribution is calculated based on small-angle scattering theory. When I(q) shows a characteristic peak and the peak intensity increases significantly with decreasing temperature, it is determined that phase separation has occurred. Molecular chain diffusion coefficient (D): The diffusion coefficient of the molecular chains of rubber A and rubber B is calculated by mean square displacement. When the difference between the diffusion coefficients of the two rubbers is ≥ one order of magnitude, the phase regions are considered to be completely separated. Step 5: Extract the cloud point temperature and swirl line temperature under different ratios, and draw the phase diagram of the blend system.
[0006] Preferably, the homopolymer rubber mentioned in step one includes any two of natural rubber, butadiene rubber, styrene-butadiene rubber, and ethylene propylene rubber.
[0007] Preferably, the molecular structure parameters in step one include the repeating unit structure of rubber A and rubber B, the degree of polymerization of molecular chains, the type and degree of substitution of side groups, and the molecular chain flexibility parameters; the aggregated state structure parameters include the crosslinking density and molecular chain entanglement molecular weight of rubber A and rubber B; and the thermodynamic parameters include the glass transition temperature and molar volume of rubber A and rubber B.
[0008] Preferably, the minimum energy algorithm in step two includes the steepest descent method, the conjugate gradient method, and the quasi-Newton method, and the minimum energy algorithm adopts a combination of the steepest descent method and the conjugate gradient method.
[0009] Preferably, the number of molecular chains in the coarse-grained blending model in step two is 1000-5000, and the mass ratio of rubber A and rubber B in the coarse-grained blending model is set according to a gradient, with the number of gradients being 5-10.
[0010] Preferably, the C-C bond torsional potential energy in step three is calculated and corrected using the DFT / B3LYP / 6-31G* method, and the deviation between the corrected bond torsional energy barrier and the experimental value is ≤5%.
[0011] Preferably, the molecular dynamics simulation temperature range in step four is from min(TgA, TgB)-50℃ to max(TgA, TgB)+200℃, the molecular dynamics simulation temperature gradient is 5-10℃, the molecular dynamics simulation pressure is set to 101.325kPa, and the total duration of the molecular dynamics simulation is 50-100ns.
[0012] Preferably, the monitoring frequency in step four is set by a fixed time interval, and the monitoring frequency is set to 1 ns.
[0013] Preferably, the molecular simulation software in step four is LAMMPS, which is compatible with multiple force fields.
[0014] The beneficial effects of this invention are as follows: By introducing crosslinking density and random crosslinking algorithms into a coarse-grained model, and incorporating structural parameters such as molecular chain entanglement, the model compensates for the neglect of the influence of key structures in existing simulations, and reduces phase separation temperature and phase region boundary errors. The force field is specifically modified and verified by Tg, improving the calculation accuracy of intermolecular interactions. Combining the advantages of multi-parameter monitoring and simulation efficiency, the model reduces dependence on experiments, shortens the cycle, and lowers costs, making it more suitable for the phase diagram research needs of tire rubber blend systems. Attached Figure Description
[0015] Figure 1 This is a schematic diagram of the process of the present invention. Detailed Implementation
[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0017] like Figure 1 As shown in the figure, this embodiment of the invention provides a method for calculating the phase diagram of a homopolymer rubber binary blend system using computer simulation. The specific steps are as follows: Step 1: Obtain the basic parameters of the homopolymer rubber binary blend system The two homopolymer rubber components of the blend system are identified, denoted as rubber A and rubber B. The molecular structure parameters, aggregate state structure parameters and thermodynamic parameters are obtained through experimental determination or molecular structure analysis. Step 2: Based on the molecular structure parameters obtained in Step 1, the molecular chains of rubber A and rubber B are coarsened using a repeating unit and coarse-grained site mapping strategy. According to the crosslinking density, crosslinking points are introduced between the molecular chains through a random crosslinking algorithm to construct a coarse-grained blending model. Representative local regions in the coarse-grained model are selected, and the coarse-grained sites are restored to the full-atom structure through the inverse mapping algorithm to obtain the full-atom blend model. At the same time, the energy minimization algorithm is used to optimize the structure of the full-atom model and eliminate unreasonable spatial steric hindrance between atoms. Step 3: Optimize the force field parameters of the rubber blend system 3.1 Preliminary selection of force field: Based on the general polymer force field COMPASS II, the all-atom blending model constructed in step two is imported; 3.2 Force field parameter correction: The torsional potential energy of the C-C bonds in the rubber molecular chain was corrected by combining quantum chemical calculation results; the van der Waals interaction parameters between the rubber side groups and the main chain were corrected by fitting density data at different temperatures through molecular dynamics simulations and adjusting the Lennard-Jones potential energy parameters so that the deviation between the simulated density and the experimental density was ≤3%. 3.3 Verification of the effectiveness of the force field: Molecular dynamics simulations were performed on a single rubber component using the modified force field to calculate its glass transition temperature Tg. If the deviation between the simulated Tg and the experimental Tg is ≤2℃, the force field parameters are qualified; otherwise, step 3.2 is repeated for iterative correction. Step 4: Import the coarse-grained blending model constructed in Step 2 into molecular simulation software, and use the NPT ensemble to perform molecular dynamics simulations of the coarse-grained model at multiple temperature gradients; during the simulation, record the following phase behavior characteristic parameters according to the set monitoring frequency: Density fluctuation parameter (Δρ): The phase separation trend is characterized by calculating the density standard deviation of a local region of the system. When Δρ ≥ 0.02 g / cm³, phase separation is determined to have occurred. Scattering intensity parameter (I(q)): The scattering intensity distribution is calculated based on small-angle scattering theory. When I(q) shows a characteristic peak and the peak intensity increases significantly with decreasing temperature, it is determined that phase separation has occurred. Molecular chain diffusion coefficient (D): The diffusion coefficient of the molecular chains of rubber A and rubber B is calculated by mean square displacement. When the difference between the diffusion coefficients of the two rubbers is ≥ one order of magnitude, the phase regions are considered to be completely separated. Step 5: Extract the cloud point temperature and swirl line temperature under different ratios, and draw the phase diagram of the blend system.
[0018] Compared to experimental determination methods, this method significantly reduces costs and time, can cover difficult experimental conditions such as extreme temperatures, reduces interference from sample purity, and yields more stable results. Compared to ordinary computer simulation methods, it achieves more accurate force field verification by correcting bond torsion potential energy, van der Waals parameters, and Tg. Coarse-grained efficiency improvement combined with full-atomic local detail preservation balances efficiency and accuracy. Multi-parameter monitoring makes the phase diagram more comprehensive, overcoming the limitations of single parameters.
[0019] In step one, the homopolymer rubber includes any two of the following: natural rubber, butadiene rubber, styrene-butadiene rubber, and ethylene-propylene rubber.
[0020] Since natural rubber, butadiene rubber, styrene-butadiene rubber, and ethylene propylene rubber are the most commonly used basic homopolymer rubbers in the rubber industry, covering the core categories of general-purpose rubbers, any combination of two can be adapted to the blending needs of multiple fields such as tires, seals, and pipes. There is no need to readjust the method framework for specific rubbers, which greatly improves the industry versatility and application scope of this simulation method.
[0021] In step one, the molecular structure parameters include the repeating unit structure of rubber A and rubber B, the degree of polymerization of molecular chains, the type of side groups and the degree of substitution, and the molecular chain flexibility parameters. The aggregated state structure parameters include the crosslinking density of rubber A and rubber B and the molecular weight of molecular chain entanglement. The thermodynamic parameters include the glass transition temperature and molar volume of rubber A and rubber B.
[0022] This design can systematically reflect the correlation between molecular structure, aggregation state, and thermodynamics, improve simulation accuracy, provide multi-dimensional data support for predicting the behavior of blended phases, and ensure the accuracy and reliability of phase diagram drawing.
[0023] In step two, the minimum energy algorithm includes the steepest descent method, the conjugate gradient method, and the quasi-Newton method. The minimum energy algorithm adopts a combination of the steepest descent method and the conjugate gradient method.
[0024] When the two algorithms are used in combination, the steepest descent method can be used first for an initial search to quickly narrow the search range and approach the minimum region; then the conjugate gradient method can be switched to take advantage of its efficient convergence characteristics when approaching the minimum value to further accurately solve for the minimum energy value. This combination method can give full play to the advantages of the two algorithms and improve the efficiency and accuracy of energy minimization.
[0025] In step two, the number of molecular chains in the coarse-grained blending model is 1000-5000, and the mass ratio of rubber A and rubber B in the coarse-grained blending model is set according to a gradient, with the number of gradients being 5-10.
[0026] Setting the number of subchains to 1000-5000 allows for a relatively realistic simulation of the molecular behavior of homopolymer rubber binary blends while ensuring computational efficiency. Setting the mass ratio of rubber A and rubber B according to gradients, with 5-10 gradients, enables a comprehensive exploration of the phase behavior of the blend system under different ratios. By setting multiple gradients, the evolution of the phase diagram of the blend system can be observed more meticulously as the ratio of rubber A and rubber B changes.
[0027] In step three, the torsional potential energy of the C-C bond is calculated and corrected using the DFT / B3LYP / 6-31G* method. After correction, the deviation between the bond torsional energy barrier and the experimental value is ≤5%.
[0028] Correcting the C-C bond torsional potential energy using the DFT / B3LYP / 6-31G* method can effectively improve the accuracy of the force field parameters. By controlling the deviation between the corrected bond torsional energy barrier and the experimental value within ≤5%, the force field parameters can be made more consistent with the actual situation. This helps to more accurately describe the motion and interaction of molecules in rubber blends in molecular dynamics simulations, thereby improving the accuracy of phase diagram simulation calculations.
[0029] In step four, the molecular dynamics simulation temperature range is from min (TgA, TgB)-50℃ to max (TgA,TgB)+200℃, the molecular dynamics simulation temperature gradient is 5-10℃, the molecular dynamics simulation pressure is set to 101.325kPa, and the total molecular dynamics simulation duration is 50-100ns.
[0030] Setting the molecular dynamics simulation temperature range from min(TgA, TgB)-50℃ to max(TgA, TgB)+200℃ covers the temperature range of various states of the homopolymer rubber binary blend system, from the glassy state to the high-elasticity state, thus comprehensively studying the influence of temperature on the phase diagram. Setting a temperature gradient of 5-10℃ can capture the effect of temperature changes on the phase behavior of the blend system more precisely, avoiding the omission of important phase transition information due to excessively large temperature gradients. Setting the total duration of the molecular dynamics simulation to 50-100ns allows the system sufficient time to reach a relatively stable state, thereby accurately simulating the phase behavior and phase diagram characteristics of the blend system.
[0031] In step four, the monitoring frequency is set using a fixed time interval, with the monitoring frequency set to 1 ns.
[0032] This design allows for timely capture of phase behavior changes in the blended system during simulation without generating excessive redundant data. Moreover, the fixed time interval setting method has good regularity and repeatability, which facilitates subsequent analysis and processing of the simulation data.
[0033] In step four, the molecular simulation software used is LAMMPS, which is compatible with multiple force fields.
[0034] LAMMPS possesses high-efficiency computing power, enabling it to complete large-scale molecular dynamics simulations within a reasonable timeframe. Its parallel computing capabilities fully leverage the advantages of multi-core processors, accelerating the simulation speed and allowing for the rapid completion of phase diagram simulations for homopolymer rubber binary blend systems.
[0035] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.
[0036] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.
Claims
1. A method for calculating a phase diagram of a homopolymer binary blend system using computer simulation, characterized by, The specific steps are as follows: Step one: Obtain the basic parameters of the homopolymer rubber binary blend system Determine the two homopolymer rubber components of the blend system, denoted as rubber A and rubber B, and obtain the molecular structure parameters, aggregate structure parameters, and thermodynamic parameters through experimental determination or molecular structure analysis. Step two: Based on the molecular structure parameters obtained in step one, use the repeating unit and coarse-grained site mapping strategy to coarse-grain the molecular chains of rubber A and rubber B. According to the crosslinking density, introduce crosslinking points between the molecular chains through a random crosslinking algorithm to construct a coarse-grained blend model. Select a representative local area in the coarse-grained model and restore the coarse-grained sites to full-atom structures through a reverse mapping algorithm to obtain a full-atom blend model. Simultaneously, use an energy minimization algorithm to optimize the full-atom model and eliminate unreasonable spatial steric hindrance between atoms. Step three: Optimize the force field parameters of the rubber blend system 3.1 Force field preliminary selection: Based on the universal polymer force field COMPASS II, import the full-atom blend model constructed in step two. 3.2 Force field parameter correction: For the C-C bond torsion potential of rubber molecular chains, modify it based on quantum chemical calculation results. For the van der Waals interaction parameters between rubber side groups and main chains, adjust the Lennard-Jones potential parameters by fitting density data at different temperatures through molecular dynamics simulation, so that the simulated density deviates from the experimental density by ≤3%. 3.3 Force field effectiveness verification: Perform molecular dynamics simulation on a single rubber component using the modified force field, calculate its glass transition temperature Tg, and if the simulated Tg deviates from the experimental Tg by ≤2°C, the force field parameters are qualified. Otherwise, repeat step 3.2 for iterative correction. Step four: Import the coarse-grained blend model constructed in step two into the molecular simulation software and perform multi-temperature gradient molecular dynamics simulation on the coarse-grained model using the NPT ensemble. During the simulation, record the following phase behavior characteristic parameters at the specified monitoring frequency: Density fluctuation parameter (Δρ): Characterize the phase separation trend by calculating the density standard deviation of the local area, and Δρ≥0.02 g / cm³ is determined as phase separation occurring. Scattering intensity parameter (I (q)): Calculate the scattering intensity distribution based on small-angle scattering theory, and when I (q) has a characteristic peak and the peak intensity significantly increases as the temperature decreases, it is determined that phase separation occurs. Molecular chain diffusion coefficient (D): Calculate the diffusion coefficients of rubber A and rubber B molecular chains through mean square displacement, and when the diffusion coefficients of the two rubbers differ by ≥ one order of magnitude, it is determined that the phase regions are completely separated. Step five: Extract the cloud point temperature and spinodal temperature at different ratios and plot the phase diagram of the blend system.
2. The method of calculating the phase diagram of a homopolymer binary blend system using computer simulation according to claim 1, characterized in that: The homopolymer rubbers mentioned in step one include any two of natural rubber, butadiene rubber, styrene-butadiene rubber, and ethylene-propylene rubber.
3. The method for calculating the phase diagram of a homopolymer rubber binary blend system using computer simulation according to claim 1, characterized in that: The molecular structure parameters in step one include the repeating unit structure, molecular chain polymerization degree, side group type and substitution degree of rubber A and rubber B, and the molecular chain flexibility parameters, the aggregate structure parameters include the crosslinking density and molecular chain entanglement molecular weight of rubber A and rubber B, and the thermodynamic parameters include the glass transition temperature and molar volume of rubber A and rubber B.
4. The method of calculating the phase diagram of a homopolymer binary blend system using computer simulation according to claim 1, characterized in that: The energy minimization algorithm in step two includes the steepest descent method, conjugate gradient method and quasi-Newton method, and the energy minimization algorithm adopts the combination of the steepest descent method and conjugate gradient method.
5. The method of calculating the phase diagram of a homopolymer binary blend system using computer simulation according to claim 1, characterized in that: The number of molecular chains in the coarse-grained blending model in step two is 1000-5000, the mass ratio of rubber A and rubber B in the coarse-grained blending model is set by gradient, and the number of the gradient is 5-10.
6. The method of calculating the phase diagram of a homopolymer binary blend system using computer simulation according to claim 1, characterized in that: The C-C bond torsion potential in step three is corrected by DFT / B3LYP / 6-31G* method, and the deviation of the corrected bond torsion energy barrier from the experimental value is ≤5%.
7. The method of calculating the phase diagram of a homopolymer binary blend system using computer simulation according to claim 1, characterized in that: The temperature range of the molecular dynamics simulation in step four is min (TgA, TgB)-50℃ to max (TgA, TgB)+200℃, the temperature gradient of the molecular dynamics simulation is 5-10℃, the pressure of the molecular dynamics simulation is set to 101.325kPa, and the total time length of the molecular dynamics simulation is 50-100ns.
8. The method of calculating the phase diagram of a homopolymer binary blend system using computer simulation according to claim 1, characterized in that: The setting mode of the monitoring frequency in step four adopts fixed time interval setting, and the monitoring frequency is set to 1ns.
9. The method of using computer simulation to calculate the phase diagram of a homopolymer binary blend system according to claim 1, characterized in that: The molecular simulation software in step four adopts LAMMPS, and the LAMMPS is compatible with multiple force fields.