A microcosmic all-atom composite model interface thickness acquisition method

Abstract

This invention discloses a method for obtaining interface thickness parameters based on a microscopic all-atom composite model, belonging to the field of molecular simulation. First, using MS software, a periodic model of polymer A and polymer B with local energy minimization is constructed. After combining the two, geometric optimization and kinetic equilibrium optimization are performed to obtain a globally energy-minimized all-atom composite model. Finally, using secondary programming techniques in the Perl script module of MS software, the atomic concentration distribution data points of the all-atom composite model are calculated, the atomic concentration distribution curve is plotted, and smoothing is performed. A criterion for determining the presence of interface thickness in the all-atom composite model is set to determine whether interface thickness exists. A formula for calculating the interface thickness of the all-atom composite model is defined to calculate the interface thickness of the all-atom composite model with interface thickness, thereby quickly, efficiently, accurately, and quantitatively calculating the interface layer thickness of the polymer composite material. Furthermore, this invention also has the advantages of convenient operation.

Description

Technical Field

[0001] This invention belongs to the field of molecular simulation technology, specifically relating to a method for automatically obtaining the thickness of the interface layer based on a microscopic all-atom model. Background Technology

[0002] The interface, acting as a "bridge" connecting the reinforcement and the matrix, is a crucial microstructure in composite materials, significantly influencing their physical and mechanical properties. Therefore, the importance of composite material interfaces has garnered widespread attention, with many countries undertaking research and structural optimization design of interfacial microregions to fully explore the enormous potential of composite materials and produce composites with superior overall performance.

[0003] Interfacial layer thickness is a core physical parameter characterizing the bonding state of a two-phase interface. It is defined as the vertical scale (width) of the three-dimensional region at the interface where the properties of one phase continuously transition from bulk phase characteristics to those of the other when two phases are in contact. For example, in their paper "Neutron reflection investigation of the interface between an immiscible polymer pair" published in *Polymer* 1988, vlo29, 1923-1927, M.L. Fernandez et al. proposed that the interfacial layer thickness between polystyrene and polymethyl methacrylate should not exceed 20 ± 5 Å.

[0004] Precise measurement of the interfacial layer thickness is crucial. Common methods include direct observation using transmission electron microscopy, nanomechanical mapping, and molecular dynamics (MD) simulations. Studies have shown that the interfacial layer thickness is closely related to the overall performance of composite materials. Taking the carbon fiber / epoxy resin system as an example, after plasma surface treatment, the interfacial layer thickness can be significantly increased to 80-150 nanometers, accompanied by a 40-60% increase in interfacial shear strength. Therefore, optimizing the interfacial layer thickness by controlling parameters such as surface treatment processes and curing conditions is a key approach to improving the performance of composite materials.

[0005] Molecular dynamics simulations are used to quantitatively characterize the interface layer thickness. This is mainly achieved by constructing a two-phase all-atom composite model, performing molecular dynamics simulations to obtain the equilibrium configuration, and then calculating the number density or mass concentration distribution curves of atoms / groups along the direction perpendicular to the interface (usually the Z-axis). A typical method for determining the interface thickness is the concentration intersection method, which takes the vertical distance between the intersection points of the concentration distribution curves of one phase and the other phase as the interface layer thickness.

[0006] To improve computational accuracy, it is usually necessary to smooth the original concentration distribution data and perform interpolation calculations, taking into account temperature effects. Studies have confirmed that the error between the interface thickness obtained by MD simulation and the TEM measured value can be controlled within 5%. It not only provides thickness values, but also reveals the microscopic interaction mechanisms such as molecular orientation, hydrogen bond network, and chemical bonding at the interface, providing important theoretical guidance for interface optimization design.

[0007] However, existing methods for obtaining interface thickness based on molecular simulations have the following significant drawbacks:

[0008] 1. High reliance on manual operation and subjectivity: Traditional workflows require researchers to manually export concentration distribution data from MS software to third-party analysis software for curve plotting and intersection analysis. Determining the "effective intersection region" of two concentration curves relies heavily on the researcher's experience and subjective judgment, resulting in differences of up to ±15% in the analysis results of the same set of data from different operators, lacking objective standards.

[0009] 2. Fragmented workflow and lack of integration: The entire analysis process is completed in separate software environments: model building → molecular dynamics simulation → data processing and analysis. It is impossible to achieve a unified closed-loop operation of "modeling-simulation-analysis" within the MS platform.

[0010] 3. Inefficiency: Due to the large number of manual steps involved, it usually takes researchers 2-3 hours to complete the analysis of a single composite model.

[0011] Currently, there are no publicly reported methods for achieving fully automated acquisition of interface thickness parameters for all-atom models within molecular simulation software platforms. Summary of the Invention

[0012] The technical problem to be solved by the present invention is to provide an automatic method for obtaining the interface layer thickness based on a microscopic all-atom model, which can quickly, accurately, objectively and quantitatively calculate the interface layer thickness of fiber / resin composite materials.

[0013] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: First, using MS software, periodic models of polymer A and polymer B with local energy minimization are constructed. After combining the two, geometric optimization and kinetic equilibrium optimization are performed to obtain a global energy minimization all-atom composite model. Finally, in the Perl script module of MS software, secondary programming technology is used to calculate the atomic concentration distribution data points of the all-atom composite model. After fitting the data points with a polynomial function, an atomic concentration distribution curve is plotted. The InlinePython command is used to call the UnivariateSpline statement to smooth the curve and reduce the influence of thermal noise. A criterion for judging the existence of interface thickness in the all-atom composite model is set. Based on the smoothed atomic concentration distribution curve of the all-atom composite model, it is determined whether the all-atom composite model has interface thickness. A formula for calculating the interface thickness of the all-atom composite model is defined, and the interface thickness of the all-atom composite model with interface thickness is calculated accordingly, thereby achieving the purpose of the present invention.

[0014] This invention relates to a method for obtaining interface thickness based on a microscopic all-atom composite model, the operation steps of which are as follows:

[0015] 1) Construct a periodic model for polymer A and polymer B that minimizes local energy.

[0016] d. Using MS software, construct monomer molecular models of polymer A and polymer B based on actual molecular structures;

[0017] e. Based on the stoichiometric ratio of polymer A and polymer B in the all-atom composite model, construct appropriate numbers of polymer A and polymer B molecular chains respectively;

[0018] f. Pack the constructed polymer A and polymer B molecular chains into a single unit cell to construct periodic models of polymer A and polymer B;

[0019] 2) Construct a global energy minimization all-atom composite model

[0020] Using MS software, the periodic models of polymer A and polymer B constructed in step 1) are combined to construct an all-atom composite model;

[0021] 3) Obtain the interface thickness value of the all-atom composite model.

[0022] In Microsoft's Perl scripting module, use the Perl language for secondary programming to perform the following operations:

[0023] a. Calculate the atomic concentration distribution data points of the all-atom composite model.

[0024] Use a for loop to iterate through all atoms of polymer A and polymer B in the all-atom composite model; use the command my $results = Modules -> Forcite -> Analysis -> ConcentrationProfile to call the built-in concentration profile command in MS to calculate the atomic concentration distribution data points of polymer A and polymer B along the direction perpendicular to the interface of the all-atom composite model.

[0025] b. Curve drawing and smoothing

[0026] Use the read statement to read the two sets of atomic concentration distribution data points obtained in step 3)a, apply a polynomial function to fit the data and plot the atomic concentration distribution curve of the all-atom composite model; use the InlinePython command to call the UnivariateSpline statement to smooth the curve and reduce the influence of thermal noise.

[0027] c. Determine if an interfacial thickness exists in the all-atom composite model.

[0028] In the atomic concentration distribution curve of the all-atom composite model, the maximum value X is taken from the region X on the left side of the curve where the Y-axis is greater than 0. max The minimum value X in the region where the Y-axis of the curve on the right is greater than 0. min Use if and else statements to determine X max Greater than X min If the condition is met, the all-atom composite model has an interface thickness, and the program proceeds to the next step to calculate the interface thickness value of the all-atom composite model; otherwise, the all-atom composite model does not have an interface thickness, and the program terminates.

[0029] d. Obtain the interface thickness value of the all-atom composite model.

[0030] In Perl script modules, X is defined using `define`. max This refers to the region where the Y-axis of the left curve in the all-atom composite model atomic concentration distribution curve is greater than 0, and the maximum value of X. min This refers to the region where the Y-axis of the right-hand curve of the all-atom composite model atomic concentration distribution curve is greater than 0, and the minimum value of X; using my $results= $X max -$X min The command retrieves the interface thickness value of the all-atom composite model.

[0031] Preferably, before constructing the initial periodic model of the amorphous structure of polymer A and polymer B in step 1)b, the constructed monomer molecular model is first geometrically optimized to stabilize its energy.

[0032] Preferably, after constructing the initial periodic models of the amorphous structures of polymer A and polymer B in step 1)c, the constructed periodic models of polymer A and polymer B are geometrically optimized to minimize their local energy.

[0033] Preferably, after constructing the all-atom composite model in step 2), the constructed all-atom composite model is geometrically optimized to minimize its local energy; then molecular dynamics equilibrium optimization is performed to minimize its global energy.

[0034] More preferably, the geometry optimization operation is implemented using the Smart Minimizer algorithm and Geometry Optimization function of MS software.

[0035] Further preferably, the molecular dynamics equilibrium optimization includes three steps: preliminary NVT ensemble equilibration, NPT ensemble equilibration, and final NVT ensemble equilibration. The preliminary NVT ensemble equilibration is used to bring the temperature of the all-atom composite model system with local energy minimization to a set value and achieve initial relaxation. The NPT ensemble equilibration is used to simulate annealing by raising the temperature to between the glass transition temperature and melting temperature of polymer A and polymer B, promoting molecular chain relaxation and interface fusion of the all-atom composite model. Then, the temperature is lowered to room temperature at atmospheric pressure to make the density of the all-atom composite model system more reasonable. The final NVT ensemble equilibration is used to obtain the all-atom composite model with global energy minimization.

[0036] Preferably, in step 3)b, during curve plotting and smoothing, when using the InlinePython command to call the UnivariateSpline statement for curve smoothing, a penalized least squares adaptive method is used to select the smoothing factor; the selected smoothing factor must be calculated using the generalized cross-validation error to ensure the proportion R of data variability. 2 No greater than 1.

[0037] Preferably, in step 3)b, curve plotting and smoothing, after smoothing the curve by calling the UnivariateSpline statement using the InlinePython command, cubic spline interpolation is performed on the smoothed curve with a step size of no more than 0.001nm to improve the accuracy of intersection point positioning.

[0038] Preferably, in step 3)a, when calculating the atomic concentration distribution data points of the all-atom composite model, there are no fewer than 100 atomic concentration distribution data points for polymer A and polymer B.

[0039] The beneficial effects of this invention are:

[0040] 1. High degree of automation and process integration: It realizes a closed-loop operation of "modeling → simulation → analysis" within the MS software platform, completely eliminating the dependence on third-party analysis software.

[0041] 2. Improved objectivity and accuracy: By replacing subjective human judgment with an adaptive intersection recognition algorithm, the human difference in the results is eliminated, significantly improving the objectivity, consistency and accuracy of the interface thickness calculation results.

[0042] 3. Significantly improved efficiency: The analysis time for a single composite model is greatly reduced from 2-3 hours of manual operation to minutes, which greatly improves research efficiency and is especially suitable for high-throughput screening and parameter optimization research.

[0043] 4. Easy to operate: By integrating automated scripts into MS's script menu, the entire analysis process can be triggered with a "one-click" action, greatly reducing the barrier to entry and technical complexity.

[0044] 5. Microscopic mechanism insights: While rapidly obtaining thickness data, it retains the ability to study the microstructure of interfaces through molecular simulation. Attached Figure Description

[0045] Figure 1 This is a schematic diagram of a polystyrene / polymethyl methacrylate composite model;

[0046] Figure 2 This is a flowchart illustrating the operation of the method for obtaining the interface thickness of a composite model based on a microscopic all-atom model according to the present invention.

[0047] Figure 3 The atomic concentration distribution curves are for the polystyrene / polymethyl methacrylate composite model. Detailed Implementation

[0048] The present invention will be further described in detail below with reference to specific embodiments. It should be emphasized that the following embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the scope of protection of the claims of the present invention.

[0049] In this invention, TPC refers to terephthaloyl chloride, DAPBI refers to 5(6)-amino-2-(4-aminobenzene)benzimidazole, and PPD refers to p-phenylenediamine.

[0050] Example 1

[0051] The interfacial thickness of the polystyrene / polymethyl methacrylate composite is as follows: Figure 1 As shown, this embodiment utilizes the commercial software Materials Studio (MS) and its Perl script interface for secondary development to calculate the interface thickness. The operation process is as follows: Figure 2 As shown, the specific steps are as follows:

[0052] Step 1: Construct a periodic model of polystyrene using MS software

[0053] a. Use the Build module to construct a styrene monomer molecular model based on the actual molecular structure.

[0054] b. The Smart Minimizer algorithm was used to perform geometric optimization on the styrene monomer molecular model to obtain an energy-stable styrene monomer molecular configuration.

[0055] c. Based on the energy-stable monomer molecular configuration, use the Build module to construct 10 polystyrene molecular chains with a degree of polymerization of 10.

[0056] d. Using the Amorphous Cell module, pack 10 polystyrene molecular chains into a single cell to construct an initial periodic model of the amorphous structure of polystyrene.

[0057] e. The Smart Minimizer algorithm is used to perform geometric optimization on the initial periodic model of polystyrene amorphous structure to obtain a polystyrene periodic model with local energy minimization.

[0058] Step 2: Construct a periodic model of polymethyl methacrylate using MS software.

[0059] a. Using the Build module, construct a molecular model of methyl methacrylate monomer with a degree of polymerization of 10 based on the actual molecular structure.

[0060] b. The Smart Minimizer algorithm is used to perform geometric optimization on the methyl methacrylate monomer molecular model to obtain an energy-stable methyl methacrylate monomer molecular configuration.

[0061] c. Based on the energy-stable monomer molecular configuration, use the Build module to construct 10 polymethyl methacrylate molecular chains.

[0062] d. Using the Amorphous Cell module, pack 10 polymethyl methacrylate molecular chains into a single cell to construct an initial periodic model of the amorphous structure of polymethyl methacrylate.

[0063] e. The Smart Minimizer algorithm is used to perform geometric optimization on the initial periodic model of polymethyl methacrylate (PMMA) amorphous structure, thereby obtaining a PMMA periodic model with local energy minimization.

[0064] Step 3: Construct a global energy minimization model for the polystyrene / polymethyl methacrylate composite using MS software.

[0065] a. Using the Confined Layer function in MS, combine the polystyrene periodic model obtained in step 1 with the polymethyl methacrylate periodic model obtained in step 2 to form an initial polystyrene / polymethyl methacrylate composite model.

[0066] b. The Geometry Optimization function was used to perform geometric optimization on the initial polystyrene / polymethyl methacrylate composite model to form a polystyrene / polymethyl methacrylate composite model with local energy minimization, and the structure was initially reasonable.

[0067] c. Molecular dynamics equilibrium optimization:

[0068] i. Preliminary Equilibrium of the NVT Ensemble: The ensemble is set as NVT, the temperature control method is Nose, and the temperature is 298 K. Preliminary kinetic equilibrium is achieved for the polystyrene / polymethyl methacrylate composite model with local energy minimization. The aim is to allow the system temperature to reach the set value and achieve preliminary relaxation.

[0069] ii. NPT ensemble balance:

[0070] Set the ensemble to NPT, temperature control method to Nose, pressure control method to Berendsen, and pressure to 10. -4 GPa.

[0071] Phase 1: Temperature 298 K, running for 200 ps, ​​used for structural optimization of the initially relaxed polystyrene / polymethyl methacrylate composite model.

[0072] Phase 2: Heat to 800 K and run for 200 ps to simulate annealing, promoting molecular chain relaxation and interface fusion of the polystyrene / polymethyl methacrylate composite model.

[0073] Phase 3: Cooling back to 298 K and running for 200 ps. This phase is conducted at atmospheric pressure to bring the density of the polystyrene / polymethyl methacrylate composite model to a reasonable level.

[0074] iii. NVT Ensemble Final Equilibrium: Set the ensemble as NVT, the temperature control method as Nose, and the temperature as 298 K. Equilibrate the polystyrene / polymethyl methacrylate composite model after NVT ensemble equilibrium for 500 ps. Set the initial velocity to Current, with a time step of 1 fs. Output one frame of configuration every 5000 steps. Monitor the temperature, total energy, and density changes of the system in real time. When the fluctuations of these physical quantities stabilize within ±10% and persist for 100 ps, ​​the system is considered to have reached equilibrium. The configuration obtained at this point is the global energy minimization polystyrene / polymethyl methacrylate composite model.

[0075] Step 4: Utilize the secondary development capabilities of MSPerl scripts to calculate the concentration distribution and interface thickness values ​​of the polystyrene / polymethyl methacrylate composite model.

[0076] Using the Perl scripting module in Microsoft, perform secondary programming with the Perl language to accomplish the following operations:

[0077] a. Calculate the atomic concentration distribution data points of the polystyrene / polymethyl methacrylate composite model.

[0078] The for loop iterates through all atoms representing the polystyrene and polymethyl methacrylate phases defined in the polystyrene / polymethyl methacrylate composite model. The built-in concentration profile command in MS is invoked via the command `my $results = Modules -> Forcite -> Analysis -> ConcentrationProfile`. This automatically calculates 100 atomic concentration distribution data points for each of the polystyrene and polymethyl methacrylate phases along the direction perpendicular to the polystyrene / polymethyl methacrylate composite model interface (Z-axis in this example), and outputs the data to be stored within MS or in a specified file.

[0079] b. Curve drawing and smoothing

[0080] The Read statement is used to read the two sets of concentration distribution data points obtained in step 4a. A polynomial function is applied to perform least-squares fitting of the data points, and the atomic concentration distribution curve of the polystyrene / polymethyl methacrylate composite model is plotted, with the X-axis representing distance and the Y-axis representing atomic concentration. Figure 3 As shown. Then, the InlinePython command is used to call the UnivariateSpline statement to smooth the curve and reduce the influence of thermal noise. The smoothing factor used in smoothing the curve is adaptively selected using penalized least squares. After selection, the error is verified by calculating the generalized cross-validation method to ensure that the proportion of data variability R is maintained. 2 The smoothing factor selected in this embodiment is 0.1, which is no greater than 1. Finally, cubic spline interpolation is performed on the smoothed curve with a step size of 0.001nm to improve the accuracy of intersection point positioning.

[0081] c. Determine if the polystyrene / polymethyl methacrylate composite model has an interfacial thickness.

[0082] In the atomic concentration distribution curve diagram of the polystyrene / polymethyl methacrylate composite model, the curve on the left is the fitted curve of the atomic concentration distribution of the polymethyl methacrylate phase. In the region where the Y-axis > 0, the maximum value of X is X. max The value is 60 Å; the curve on the right is the fitted curve of the atomic concentration distribution of polystyrene. In the region where the Y-axis > 0, the minimum value of X is X. minIt is 45 Å. Use if and else statements to determine X. max Greater than X min The calculation checks whether the condition is met. If it is met, an intersection region exists, meaning the polystyrene / polymethyl methacrylate composite model has an interface thickness, and the process proceeds to the next step to calculate the interface thickness value of the all-atom composite model. If it is not met, the polystyrene / polymethyl methacrylate composite model does not have an interface thickness, and the calculation program terminates. The polystyrene / polymethyl methacrylate composite model X in this embodiment... max Greater than X min If the interface thickness is established, proceed to the next step to calculate the interface thickness value of the polystyrene / polymethyl methacrylate composite model.

[0083] d. Obtain the interface thickness value of the polystyrene / polymethyl methacrylate composite model.

[0084] In Perl script modules, X is defined using `define`. max This refers to the region where the Y-axis of the left curve of the polystyrene / polymethyl methacrylate composite model is greater than 0, and the maximum value of X. min This represents the minimum X value in the region where the Y-axis of the right curve of the polystyrene / polymethyl methacrylate composite model atomic concentration distribution curve is greater than 0. Using `my $results = $X`... max -$X min The calculated interface thickness of the polystyrene / polymethyl methacrylate composite model is 15 Å.

[0085] In this embodiment, the time to obtain the interface thickness of a single polystyrene / polymethyl methacrylate composite model is only 2 minutes, which greatly shortens the acquisition time and improves the research efficiency compared with the 2-3 hours of manual operation. The interface layer thickness of the polystyrene / polymethyl methacrylate composite model obtained in this embodiment is consistent with the measured interface layer thickness range.

[0086] Example 2

[0087] This embodiment uses a heterocyclic aramid amorphous unit cell model with a degree of polymerization of 10 and 10 molecular chains, prepared from TPC, DAPBI, and PPD monomers, and a phenolic resin amorphous unit cell model with a degree of polymerization of 12 as examples. The interface thickness is calculated using the MaterialsStudio (MS) commercial software and its Perl script interface secondary development capabilities. The operation process is as follows:

[0088] Step 1: Construct a periodic model of heterocyclic aramid fibers using MS software.

[0089] a. Use the Build module to construct a monomeric molecular model formed by combining DAPBI, TPC, and PPD based on the actual molecular structure.

[0090] b. The Smart Minimizer algorithm is used to perform geometric optimization on the monomer molecule model to obtain an energy-stable monomer molecule configuration.

[0091] c. Based on the energy-stable monomer molecular configuration, use the Build module to construct 10 heterocyclic aramid molecular chains with a degree of polymerization of 10.

[0092] d. Using the Amorphous Cell module, pack 10 molecular chains into a single cell to construct a periodic initial model of the amorphous structure of heterocyclic aramid.

[0093] e. The Smart Minimizer algorithm is used to perform geometric optimization on the initial periodic model of the heterocyclic aramid amorphous structure to obtain a periodic model of heterocyclic aramid with local energy minimization.

[0094] Step 2: Construct a periodic model of the amorphous structure of phenolic resin using MS software.

[0095] a. Use the Build module to construct a phenolic resin monomer molecular model with a degree of polymerization of 12 based on the actual molecular structure.

[0096] b. The Smart Minimizer algorithm is used to perform geometric optimization on the monomer molecule model to obtain the energy-stable molecular configuration of phenolic resin monomers.

[0097] c. Based on the energy-stable monomer molecular configuration, use the Build module to construct 10 phenolic resin molecular chains.

[0098] d. Using the Amorphous Cell module, pack 10 phenolic resin molecular chains into a single cell to construct an initial periodic model of the amorphous structure of phenolic resin.

[0099] e. The Smart Minimizer algorithm is used to perform geometric optimization on the initial periodic model of the amorphous structure of phenolic resin, thereby obtaining a periodic model of phenolic resin with local energy minimization.

[0100] Step 3: Construct a global energy minimization heterocyclic aramid fiber / phenolic resin composite model using MS software.

[0101] a. Using the Confined Layer function in MS, combine the heterocyclic aramid periodic model obtained in step 1 with the phenolic resin periodic model obtained in step 2 to form an initial heterocyclic aramid fiber / phenolic resin composite model.

[0102] b. The Geometry Optimization function was used to perform geometric optimization on the initial heterocyclic aramid fiber / phenolic resin composite model to form a heterocyclic aramid fiber / phenolic resin composite model with local energy minimization, and the structure was initially reasonable.

[0103] c. Molecular dynamics equilibrium optimization

[0104] i. Preliminary Equilibrium of the NVT Ensemble: The ensemble is set as NVT, the temperature control method is Nose, and the temperature is 298 K. Preliminary kinetic equilibrium is achieved for the heterocyclic aramid fiber / phenolic resin composite model with local energy minimization. The aim is to allow the system temperature to reach the set value and achieve preliminary relaxation.

[0105] ii. NPT ensemble balance:

[0106] Set the ensemble to NPT, temperature control method to Nose, pressure control method to Berendsen, and pressure to 10. -4 GPa.

[0107] Phase 1: Temperature 298 K, running for 200 ps, ​​used for structural optimization of the initially relaxed heterocyclic aramid fiber / phenolic resin composite model.

[0108] Phase 2: Heat to 800 K and run for 200 ps to simulate annealing, promoting molecular chain relaxation and interface fusion of the heterocyclic aramid fiber / phenolic resin composite model.

[0109] Phase 3: Cooling back to 298 K and running for 200 ps. This phase is conducted at atmospheric pressure to bring the density of the heterocyclic aramid fiber / phenolic resin composite model to a reasonable level.

[0110] iii. NVT Ensemble Final Equilibrium: Set the ensemble to NVT, use the Nose temperature control method, and set the temperature to 298 K. Equilibrate the model after NPT equilibrium for 500 steps. Set the initial velocity to Current and the time step to 1 fs. Output one frame of configuration every 5000 steps. Monitor the temperature, total energy, and density changes of the system in real time. When the fluctuations of these physical quantities stabilize within ±10% and last for 100 steps, the system is considered to have reached equilibrium. The configuration obtained at this point is the globally energy-minimized heterocyclic aramid fiber / phenolic resin composite model.

[0111] Step 4: Using the secondary development capabilities of MSPerl scripts, calculate the concentration distribution and interface thickness values ​​of the heterocyclic aramid fiber and phenolic resin composite model.

[0112] Using the Perl scripting module in Microsoft, perform secondary programming with the Perl language to accomplish the following operations:

[0113] a. Calculate the concentration distribution data points of heterocyclic aramid fibers and phenolic resins.

[0114] The for loop iterates through all atoms in the heterocyclic aramid fiber / phenolic resin composite model, representing the heterocyclic aramid fiber phase and the phenolic resin phase. The built-in concentration profile command in MS is invoked via the command `my $results = Modules -> Forcite -> Analysis -> ConcentrationProfile`. This automatically calculates 200 atomic concentration distribution data points for each of the heterocyclic aramid fiber and phenolic resin phases along the direction perpendicular to the heterocyclic aramid fiber / phenolic resin interface (Z-axis in this example), and outputs the data to be stored within MS or in a specified file.

[0115] b. Curve fitting and smoothing

[0116] The two concentration distribution data points obtained in step 4a are read using the Read statement. A polynomial function is applied to perform least-squares fitting of the data points, and an atomic concentration distribution curve for the heterocyclic aramid fiber / phenolic resin composite model is plotted, with the X-axis representing distance and the Y-axis representing atomic concentration. Then, the UnivariateSpline statement is called using the InlinePython command to smooth the curve and reduce the influence of thermal noise. The smoothing factor used in smoothing the curve is adaptively selected using penalized least-squares, and after selection, the generalized cross-validation error is calculated to ensure the proportion R of data variability. 2 To approximate a value close to 1, the smoothing factor selected in this embodiment is 0.1; finally, cubic spline interpolation is performed on the smoothed curve with a step size of 0.001nm to improve the accuracy of intersection point positioning.

[0117] c. Determine if there is interfacial thickness between heterocyclic aramid fibers and phenolic resin.

[0118] In the atomic concentration distribution curve diagram of the heterocyclic aramid fiber / phenolic resin composite model, the curve on the left is the fitted curve of the atomic concentration distribution of the heterocyclic aramid fiber phase. In the region where the Y-axis > 0, the maximum value X is taken. max The value is 95 Å; the curve on the right is the fitted curve of the atomic concentration distribution of the phenolic resin phase. In the region where the Y-axis > 0, the minimum value of X is X. min It is 75Å; use if and else statements to determine X. max Greater than X min If the condition is met, an intersection region exists, meaning there is an interface thickness between the heterocyclic aramid fiber and the phenolic resin. The process then proceeds to the next step to calculate the interface thickness value of the all-atomic composite model. If the condition is not met, the heterocyclic aramid fiber / phenolic resin composite model does not have an interface thickness, and the calculation program terminates. The heterocyclic aramid fiber / phenolic resin composite model X in this embodiment... max Greater than Xmin If the interface thickness is established, proceed to the next step to calculate the interface thickness value of the heterocyclic aramid fiber / phenolic resin composite model.

[0119] d. Obtain the thickness value of the heterocyclic aramid fiber / phenolic resin interface.

[0120] In Perl script modules, X is defined using `define`. max For the atomic concentration distribution curve of the heterocyclic aramid fiber / phenolic resin composite model, the left curve represents the region where the Y-axis is greater than 0, and the maximum value of X is shown. min This represents the minimum X value in the region where the Y-axis of the right-hand curve of the atomic concentration distribution curve of the heterocyclic aramid fiber / phenolic resin composite model is greater than 0. This is achieved using `my $results = $X`. max -$X min The calculated interface thickness of the heterocyclic aramid fiber / phenolic resin composite model is 20 Å.

[0121] In this embodiment, the acquisition time for the interface thickness of a single heterocyclic aramid fiber / phenolic resin is only 3 minutes, which greatly shortens the acquisition time and improves the research efficiency compared with the 2-3 hours of manual operation. The interface layer thickness of the heterocyclic aramid fiber / phenolic resin composite material obtained in this embodiment is consistent with the measured interface layer thickness range.

Claims

1. A method for obtaining interface thickness based on a microscopic all-atom composite model, characterized in that, The operation steps are as follows: 1) Construct periodic models for polymer A and polymer B a. Using MS software, construct monomer molecular models of polymer A and polymer B based on actual molecular structural formulas; b. Based on the stoichiometric ratio of polymer A and polymer B in the all-atom composite model, construct appropriate numbers of polymer A and polymer B molecular chains respectively; c. Pack the constructed polymer A and polymer B molecular chains into a single unit cell to construct periodic models of polymer A and polymer B; 2) Constructing an all-atom composite model Using MS software, the periodic models of polymer A and polymer B constructed in step 1) are combined to construct an all-atom composite model; 3) Obtain the interface thickness value of the all-atom composite model. In Microsoft's Perl scripting module, use the Perl language for secondary programming to perform the following operations: a. Calculate the atomic concentration distribution data points of the all-atom composite model. Use a for loop to iterate through all atoms of polymer A and polymer B in the all-atom composite model; use the command my $results= Modules -> Forcite -> Analysis -> ConcentrationProfile to call the built-in concentration profile command in MS to calculate the atomic concentration distribution data points of polymer A and polymer B along the direction perpendicular to the interface of the all-atom composite model. b. Curve drawing and smoothing Use the read statement to read the two sets of atomic concentration distribution data points obtained in step 3)a, apply a polynomial function to fit the data and plot the atomic concentration distribution curve of the all-atom composite model; use the InlinePython command to call the UnivariateSpline statement to smooth the curve and reduce the influence of thermal noise. c. Determine if an interfacial thickness exists in the all-atom composite model. In the atomic concentration distribution curve of the all-atom composite model, the maximum value X is taken from the region X on the left side of the curve where the Y-axis is greater than 0. max The minimum value X in the region where the Y-axis of the curve on the right is greater than 0. min ; Use if and else statements to determine X max Greater than X min If the condition is met, the all-atom composite model has an interface thickness, and the program proceeds to the next step to calculate the interface thickness value of the all-atom composite model; if the condition is not met, the all-atom composite model does not have an interface thickness, and the program terminates. d. Obtain the interface thickness value of the all-atom composite model. In Perl script modules, X is defined using `define`. max This refers to the region where the Y-axis of the left curve in the all-atom composite model atomic concentration distribution curve is greater than 0, and the maximum value of X. min This refers to the region where the Y-axis of the right-hand curve of the all-atom composite model atomic concentration distribution curve is greater than 0, and the minimum value of X; using my $results= $X max -$X min The command retrieves the interface thickness value of the all-atom composite model.

2. The method for obtaining interface thickness based on a microscopic all-atom composite model according to claim 1, characterized in that: Before constructing the initial periodic model of the amorphous structure of polymer A and polymer B in step 1)b, the constructed monomer molecular model is geometrically optimized to stabilize its energy.

3. The method for obtaining interface thickness based on a microscopic all-atom composite model according to claim 1, characterized in that: Step 1)c After constructing the initial periodic models of the amorphous structures of polymer A and polymer B, the constructed periodic models of polymer A and polymer B are geometrically optimized to minimize their local energy.

4. The method for obtaining interface thickness based on a microscopic all-atom composite model according to claim 1, characterized in that: After constructing the all-atom composite model in step 2), the constructed all-atom composite model is geometrically optimized to minimize its local energy; then molecular dynamics equilibrium optimization is performed to minimize its global energy.

5. The method for obtaining interface thickness based on a microscopic all-atom composite model according to any one of claims 2 to 4, characterized in that: The geometry optimization operation is implemented using the Smart Minimizer algorithm and GeometryOptimization function in MS software.

6. The method for obtaining interface thickness based on a microscopic all-atom composite model according to claim 4, characterized in that: The molecular dynamics equilibrium optimization includes three steps: preliminary NVT ensemble equilibration, NPT ensemble equilibration, and final NVT ensemble equilibration. Preliminary NVT ensemble equilibration is used to bring the temperature of the all-atom composite model system, which minimizes local energy, to a set value and induces initial relaxation. NPT ensemble equilibration involves heating to between the glass transition temperature and melting temperature of polymers A and B to simulate annealing, promoting molecular chain relaxation and interface fusion in the all-atom composite model. Then, the temperature is lowered to room temperature at atmospheric pressure to bring the density of the all-atom composite model system to a reasonable level. Final NVT ensemble equilibration is used to obtain the all-atom composite model with globally minimized energy.

7. The method for obtaining interface thickness based on a microscopic all-atom composite model according to claim 1, characterized in that: Step 3)b: In curve plotting and smoothing, when using the InlinePython command to call the UnivariateSpline statement for curve smoothing, a penalized least squares adaptive method is used to select the smoothing factor. The selected smoothing factor must be calculated using the generalized cross-validation error to ensure the proportion R of data variability. 2 No greater than 1.

8. The method for obtaining interface thickness based on a microscopic all-atom composite model according to claim 1, characterized in that: In step 3)b, during curve plotting and smoothing, after smoothing the curve by calling the UnivariateSpline statement using the InlinePython command, cubic spline interpolation is performed on the smoothed curve with a step size of no more than 0.001nm to improve the accuracy of intersection point positioning.

9. The method for obtaining interface thickness based on a microscopic all-atom composite model according to claim 1, characterized in that: Step 3)a When calculating the atomic concentration distribution data points for the all-atom composite model, there should be no fewer than 100 atomic concentration distribution data points for polymer A and polymer B.

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