1. A method for predicting the glass transition temperature of a polylactic acid composite system based on materials studio is characterized by comprising the following steps:

s1) building an amorphous unit cell model of a polylactic acid system based on a Monte Carlo method;

s2) carrying out geometric optimization and annealing simulation on the constructed amorphous unit cell model to obtain a configuration with the lowest energy;

s3) carrying out kinetic calculation on the obtained energy lowest configuration to obtain a cooling simulation initial equilibrium configuration of the polylactic acid system;

s4) performing cooling simulation on the equilibrium configuration to obtain density and free volume fraction under each cooling temperature order, linearly fitting the density-temperature relationship to obtain a predicted value of glass transition temperature, and analyzing the change trend of the glass transition temperature of the polylactic acid system according to the free volume fraction.

2. The method for predicting the glass transition temperature of a polylactic acid composite system based on materials studio according to claim 1, wherein in step S1, the polymerization degree, the number, the temperature of the molecular chain and the initial parameters of the cell model are preset when the amorphous cell model is constructed; in order to eliminate the influence of non-bonded carbon atoms, the two ends of the constructed carbon nano tube are subjected to hydrogenation treatment; during geometric optimization, an optimization algorithm, the maximum convergence tolerance of the related force, energy and displacement and the maximum iteration number in the geometric optimization process are preset.

3. The method for predicting the glass transition temperature of a polylactic acid composite system based on materials studio according to claim 1, wherein the amorphous unit cell model set up in step S2 is not in the energy minimum state, and needs to be subjected to structural optimization and annealing simulation to search for the energy minimum state under global conditions; during annealing simulation, the maximum value and the minimum value of the temperature, the cycle times and the simulation duration parameters in the annealing process are preset.

4. The method for predicting the glass transition temperature of a polylactic acid composite system based on materials studio according to claim 1, wherein in step S3, the energy minimum configuration is subjected to NVT ensemble dynamics calculation to fully relax the structure and NPT ensemble dynamics calculation to optimize the structure, so that the simulated system approaches the material under real conditions.

5. The method for predicting the glass transition temperature of a polylactic acid composite system based on materials studio according to claim 1, wherein in the step S4, the initial cooling temperature and the final cooling cut-off temperature of the simulation system, the temperature difference of each stage of cooling, and the time length of each temperature step in the NVT and NPT ensemble are preset in the cooling simulation process.

6. The polylactic acid composite system glass transition temperature prediction method based on materials studio according to claim 5, characterized in that the simulated system density at each temperature step is the average value of the last n frame files close to the set temperature calculated by NPT dynamics; the free volume fraction is calculated from the balanced configuration to generate the connely surface divided free volume and the occupied volume.

7. The material studio-based polylactic acid composite system glass transition temperature prediction method according to claim 6, wherein the density and free volume fraction of the simulated system after NPT calculation at each temperature step are obtained; calculating the configuration after each stage of cooling as the initial configuration of the next stage; and obtaining the density-temperature relation of the simulation system after obtaining the densities of all cooling temperature steps, and obtaining the predicted value of the glass transition temperature of the simulation system through piecewise linear fitting.

8. The material studio-based polylactic acid composite system glass transition temperature prediction method according to claim 6, wherein the free volume fraction of each temperature step of the polylactic acid composite system is calculated based on the following formula:

wherein the content of the first and second substances,FFVis the fraction of the free volume,V _free is the free volume of the liquid to be treated,V _occupied is an occupied volume.

Background

With the increasing awareness of environmental protection, research and application of degradable materials capable of being recycled are receiving more and more attention in the aspect of environmental management. The preparation of degradable composite materials by using natural plant fiber resources has become a hot point of research of scientists at home and abroad.

Polylactic acid (PLA) is one of the most potential biodegradable materials in the aspect of application value as an artificially synthesized thermoplastic polyester material, but polylactic acid itself has poor heat resistance, and aiming at the defects, the heat resistance needs to be improved, so that the PLA can be applied to working conditions with wider working temperature, and the application range is expanded. Most of the current research on the improvement of the performance of polylactic acid is experimental research, which is time-consuming, labor-consuming and high in cost. With the rapid development of computer technology, methods for assisting in the research of experimental schemes for developing new materials by means of computer simulation have been widely used.

The molecular dynamics simulation has the unique advantage of simulating the material properties from the molecular scale, can overcome the difficulty that the surface of a sample is difficult to treat in the traditional test, and becomes an important research means in the field of materials. The molecular dynamics simulation can explain the material property from the molecular scale, also make up for the short part of the experiment, can predict the performance of the existing and non-existing materials based on the research result of the macroscopic level, and obtain the result which is difficult to obtain in the experiment, thereby guiding the experiment.

Disclosure of Invention

The invention aims to provide a material studio-based method for predicting the glass transition temperature of a polylactic acid composite system, which is favorable for conveniently and accurately predicting the glass transition temperature of the polylactic acid composite system, reduces the experiment cost and shortens the research and development period.

In order to achieve the purpose, the invention adopts the technical scheme that: a method for predicting the glass transition temperature of a polylactic acid composite system based on materials studio comprises the following steps:

s1) building an amorphous unit cell model of a polylactic acid system based on a Monte Carlo method;

s2) carrying out geometric optimization and annealing simulation on the constructed amorphous unit cell model to obtain a configuration with the lowest energy;

s3) carrying out kinetic calculation on the obtained energy lowest configuration to obtain a cooling simulation initial equilibrium configuration of the polylactic acid system;

s4) performing cooling simulation on the equilibrium configuration to obtain density and free volume fraction under each cooling temperature order, linearly fitting the density-temperature relationship to obtain a predicted value of glass transition temperature, and analyzing the change trend of the glass transition temperature of the polylactic acid system according to the free volume fraction.

Further, in the step S1, when constructing the amorphous cell model, the polymerization degree, the number, the temperature of the molecular chain and the initial parameters of the cell model are preset; in order to eliminate the influence of non-bonded carbon atoms, the two ends of the constructed carbon nano tube are subjected to hydrogenation treatment; during geometric optimization, an optimization algorithm, the maximum convergence tolerance of the related force, energy and displacement and the maximum iteration number in the geometric optimization process are preset.

Further, in step S2, the constructed amorphous cell model is not in the lowest energy state, and needs to be subjected to structural optimization and annealing simulation to search for the lowest energy state under the global condition; during annealing simulation, the maximum value and the minimum value of the temperature, the cycle times and the simulation duration parameters in the annealing process are preset.

Further, in step S3, performing a dynamic calculation under the NVT ensemble on the lowest energy configuration to obtain a fully relaxed structure and a dynamic calculation optimal structure under the NPT ensemble to make the simulation system approach the material under the real condition.

Further, in the step S4, in the cooling simulation process, an initial cooling temperature and a final cooling cut-off temperature of the simulation system, a temperature difference of each stage of cooling, and a time length of dynamic calculation of each temperature step under the NVT and NPT ensemble are preset.

Further, the simulation system density at each temperature step is the average value of the last n frame files which are close to the set temperature calculated by the NPT dynamics; the free volume fraction is calculated from the balanced configuration to generate the connely surface divided free volume and the occupied volume.

Further, obtaining the density and the free volume fraction of the simulation system after NPT calculation under each temperature step; calculating the configuration after each stage of cooling as the initial configuration of the next stage; and obtaining the density-temperature relation of the simulation system after obtaining the densities of all cooling temperature steps, and obtaining the predicted value of the glass transition temperature of the simulation system through piecewise linear fitting.

Further, the free volume fraction of each temperature step of the polylactic acid composite system is calculated based on the following formula:

wherein the content of the first and second substances,FFVis the fraction of the free volume,V _free is the free volume of the liquid to be treated,V _occupied is an occupied volume.

Compared with the prior art, the invention has the following beneficial effects: the method for predicting the glass transition temperature of the polylactic acid composite system based on materials studio is provided, an accurate composite material model can be built, the glass transition temperature of the material is predicted, and the correctness of the model building and performance prediction method is verified by comparing performance simulation result parameters with relevant experimental documents; based on the advantages of computer simulation, the experimental cost can be reduced, and the research and development period can be shortened. Meanwhile, the invention sets proper force field parameters and an optimization scheme for simulation, so that the whole simulation system is close to a material system in a real state. In addition, the invention can obtain the glass transition temperature prediction of different polylactic acid simulation systems by changing the parameters such as the length of a molecular chain, the state of the carbon nano tube, the simulation temperature condition and the like, and can more intuitively express the factors influencing the glass transition temperature of the polylactic acid system.

Drawings

FIG. 1 is a flow chart of a method implementation of an embodiment of the present invention.

FIG. 2 is a model diagram of polylactic acid monomer molecules, optimized polylactic acid molecular chains and carbon nanotubes in the embodiment of the present invention.

FIG. 3 is a schematic diagram of a dynamic equilibrium polylactic acid system in an embodiment of the present invention.

FIG. 4 is a flow chart of a cooling simulation in an embodiment of the present invention.

FIG. 5 is a Connoly surface model for calculating the fractional free volume of the polylactic acid system in the examples of the present invention.

FIG. 6 is a density-temperature curve of a simulated polylactic acid system according to an embodiment of the present invention.

FIG. 7 is a free volume fraction versus temperature curve for a polylactic acid system in an example of the present invention.

Detailed Description

The invention is described in further detail below with reference to the figures and the embodiments.

As shown in fig. 1, this embodiment provides a method for predicting a glass transition temperature of a polylactic acid composite system based on materials studio, which includes the following steps:

s1) building an amorphous unit cell model of the polylactic acid system based on the Monte Carlo method.

When an amorphous unit cell model is constructed, the polymerization degree, the number and the temperature of a molecular chain and initial parameters of the unit cell model need to be preset. In order to eliminate the influence of non-bonded carbon atoms, the two ends of the constructed carbon nano tube are subjected to hydrogenation treatment. During geometric optimization, an optimization algorithm, the maximum convergence tolerance of the related force, energy and displacement and the maximum iteration number in the geometric optimization process need to be preset.

The step S1 specifically includes the following steps:

firstly, a polylactic acid monomer molecular model is constructed as shown in fig. 2(a), a polylactic acid molecular chain with the polymerization degree of 50 is constructed through build polymers after the constructed monomer molecular model is preliminarily optimized, then, the constructed polylactic acid molecular chain is subjected to geometric structure optimization, and the optimized structure is shown in fig. 2 (b).

A (6, 6) type single-walled carbon nanotube is constructed by means of a built Nanostructure module in materials studio, the bond length is set to be 1.42A, and carbon nanotube models with different lengths are constructed by changing the axial length parameters of the carbon nanotube. This example used a carbon nanotube length of 24.6 a, as in fig. 2 (c). To prevent the effect of non-bonded carbon atoms, the carbon nanotube model was hydrotreated by Adjust Hydrogen.

Loading 20 PLA molecular chains and carbon nano tubes by means of an Amorphous Cell module of a materials studio platform according to a Monte Carlo method to construct an Amorphous unit Cell model; when a unit cell model containing the carbon nano tube is built, the mass center of the carbon nano tube is required to be coincided with the body center of the unit cell, and the axial direction of the carbon nano tube is coincided with the positive x direction; the cubic cell side length parameter was set to 50A.

The structure optimization parameters are set as follows: the optimization algorithm selects Smart, and the geometric optimization convergence precision is energy convergence tolerance 2 multiplied by 10^-5kcal/mol, force convergence tolerance of 1 × 10^-3kcal/mol/A, external pressure is not applied, and the lattice parameters are optimized while the atomic coordinates are optimized; the force field is a COMPASS II force field, charges are distributed by the force field, an EWALD algorithm and an Atom based algorithm are respectively selected for the coulomb effect and the van der Waals effect, and the EWALD algorithm is selected to be suitable because the coulomb potential is a long-range potential.

In this example, three polylactic acid systems were constructed, respectively: pure polylactic acid system (PLA), unfunctionalized carbon nanotube/polylactic acid system (p-CNTs/PLA), aminated carbon nanotube/polylactic acid system (CNTs-NH)₂/PLA). The aminated carbon nanotube is grafted with-NH by taking 6% of the carbon atoms of the carbon nanotube as grafting sites₂。

S2) carrying out geometric optimization and annealing simulation on the constructed amorphous unit cell model to obtain the configuration with the lowest energy.

The initially established amorphous unit cell model is not in the lowest energy state, and kinetic calculation can be carried out only when the lowest energy state is reached and the lowest energy configuration is obtained. And in order to reach the energy minimum state, the energy minimum state under the global condition needs to be searched by means of geometric structure optimization and annealing simulation through structure optimization and annealing simulation.

The system geometric structure optimization parameters are set as follows: selection of force field COMPASS II force field, convergence tolerance of energy and force 2 × 10 respectively^-5kcal/mol and 1X 10^-3kcal/mol/A, the maximum iteration number of the geometric optimization is set to 20000.

After the initial process of optimizing the simulation geometry, in order to prevent the simulation system from falling into the lowest point of the local energy, the global energy lowest point state is searched by means of an annealing simulation Anneal module, and the step is realized by applying the external temperature change.

During annealing simulation, parameters such as the highest value and the lowest value of the temperature, the cycle number, the simulation duration and the like in the annealing process need to be preset.

The specific parameters of the annealing simulation are set as follows: presetting a COMPASS II force field, and calculating coulomb interaction and van der Waals interaction respectively by using an EWald summation method and an Atom based summation method; setting the number of annealing cycles to be 10 under an NVT ensemble, the initial temperature to be 200K, the highest temperature to be 400K, circularly setting 20 temperature steps, wherein the kinetic calculation step number of each temperature step is 1000, the step length is 1fs, selecting an Andersen method for temperature control, and the total annealing time is 400 ps; annealing simulation allows the simulation system to overcome the energy barrier into other low energy state regions during the temperature ramp up and ramp down.

S3) carrying out kinetic calculation on the obtained energy lowest configuration to obtain the cooling simulation initial equilibrium configuration of the polylactic acid system.

After geometric optimization and annealing simulation, kinetic calculation is needed to make the simulation system approximate to the material system under the real condition. The kinetic calculation of the polylactic acid composite system model with the lowest energy is divided into two processes: NVT ensemble lower relaxation structure and NPT ensemble lower optimal structure.

The dynamic calculation parameters of the simulated system NVT ensemble lower relaxation structure are set as follows: presetting a COMPASS II force field, and calculating coulomb interaction and van der Waals interaction respectively by using an EWald summation method and an Atom based summation method; setting the temperature to 298K, the step length to 1fs, the total duration to 200ps, and outputting a frame structure file every 5000 steps of calculation; the Andersen method is selected for temperature control.

The parameters for the NPT dynamics calculation were set as: presetting a COMPASS II force field, and calculating coulomb interaction and van der Waals interaction respectively by using an EWald summation method and an Atom based summation method; temperature setting 298K, step size 1fs, pressure 1.01X 10^-4GPaThe total duration is 400ps, and a frame structure file is output every 5000 steps of calculation; respectively selecting an Andersen method and a Berendsen method by temperature and pressure control; finally, the temperature fluctuation does not exceed 10K in the 100ps calculation process, the energy fluctuation does not exceed 3 percent of the total energy value, and the structure can be considered to reach an equilibrium state.

The kinetic calculations were completed to obtain pure polylactic acid systems (PLA) as shown in FIG. 3 (a), unfunctionalized carbon nanotube/polylactic acid systems (p-CNTs/PLA) as shown in FIG. 3 (b), and aminated carbon nanotube/polylactic acid systems (CNTs-NH)₂/PLA) as in FIG. 3 (c).

S4) performing cooling simulation on the equilibrium configuration to obtain density and free volume fraction under each cooling temperature order, linearly fitting the density-temperature relationship to obtain a predicted value of glass transition temperature, and analyzing the change trend of the glass transition temperature of the polylactic acid system according to the free volume fraction.

In the cooling simulation process, the initial cooling temperature and the final cooling cutoff temperature of the simulation system, the temperature difference of each stage of cooling, and the time length of the dynamics calculation of each temperature step under the NVT and NPT ensemble need to be preset.

The simulation system density at each temperature step is the average value of the last n frame files which are close to the set temperature calculated by the NPT dynamics; the free volume fraction is calculated from the balanced configuration to generate the connely surface divided free volume and the occupied volume.

Obtaining the density and the free volume fraction of the simulation system after NPT calculation under each temperature step; calculating the configuration after each stage of cooling as the initial configuration of the next stage; and obtaining the density-temperature relation of the simulation system after obtaining the densities of all cooling temperature steps, and obtaining the predicted value of the glass transition temperature of the simulation system through piecewise linear fitting.

Specifically, the cooling simulation is performed on the simulation system by means of a Dynamics module, and the simulation process is shown in fig. 4.

Firstly, taking a configuration after dynamic calculation balance as a model for initial cooling simulation, and heating the initial simulation to 420K; and (3) heating the initial model to 420K under the NVT ensemble by virtue of a dynamics calculation module in a Forcite module of the MS platform, so as to obtain parameters of the model in a 420K temperature state, and then sequentially carrying out NVT dynamics calculation of 50ps and NPT dynamics calculation of 200 ps.

And then, gradually cooling the model to 280K at a cooling speed of 10K/250ps, namely performing dynamic calculation under an NVT ensemble of 50ps, keeping the temperature constant, performing dynamic calculation under an NPT (non-uniform stress test) under 200ps, simulating 15 temperatures in total, gradually cooling the model from 420K to 280K at an interval of 10K, and obtaining a density value after NPT balance at each temperature stage.

In order to reduce the error of density value, the density value of each cooling temperature step is the average value of the densities of 5 frame files which are the last frame files of the NPT balance and the set temperature.

The parameters of the cooling simulation process are set as follows: a COMPASS II force field is selected, the pressure is set to be 1 atmospheric pressure, the temperature control method is Andersen, the pressure control method is Berendsen, and each step starts to be calculated from the configuration which is completed by the last step of temperature reduction calculation.

The free volume fraction of each temperature step of the temperature reduction of the simulation system is calculated by constructing a Connoly surface on the simulation system, and the free volume and the occupied volume in the simulation system are calculated by the following formula:

wherein the content of the first and second substances,FFVis the fraction of the free volume,V _free is the free volume of the liquid to be treated,V _occupied is an occupied volume. The Connoly surface model is shown in fig. 5.

Cooling simulation is carried out to obtain density values under various temperature scales, a density-temperature curve is fitted in a segmented mode, and the abscissa of the intersection point of two fitting lines is the T of the simulation system_gThe value is obtained.

After the temperature reduction simulation, the density-temperature curve of the simulation system is obtained by extraction; pure polylactic acid system (PLA) as in FIG. 6 (a), unfunctionalized carbon nanotube/polylactic acid system (p-CNTs/PLA) as in FIG. 6 (b), aminated carbon nanotube/polylactic acid system (CNTs-NH)₂/PLA) as shown in FIG. 6 (c)(ii) a The free volume fraction versus temperature relationship for the polylactic acid system is shown in fig. 7.

The method for predicting the glass transition temperature of the polylactic acid composite system based on materials studio can construct an accurate composite material model, and the correctness of the construction of the model and the performance prediction method is verified by comparing performance simulation result parameters with related experimental documents. Based on the advantages of computer simulation, the experimental cost can be reduced, and the research and development period can be shortened. The invention can predict the glass transition temperature of the polylactic acid system to be researched by changing the length of a molecular chain and the state of the carbon nano tube, and intuitively represents the microscopic factors causing the glass transition temperature of the polylactic acid system by means of a model. The invention can further analyze the interface interaction from the interface state by means of a model, and further explore the properties of the material.

The details and operation of preferred embodiments of the invention are set forth in the accompanying drawings. It will be appreciated by those skilled in the art that the present invention is not limited to the examples described above. It will be apparent to those skilled in the art that various modifications and variations can be made in the details of the parameters and in the sequence of the operating steps without departing from the spirit of the invention, and the technical solutions available to those skilled in the art can be obtained by theoretical modifications and equivalent practices, all of which are intended to be covered by the scope of the claims.