Construction method and application of gene pool of high-temperature-resistant liquid crystal polymer material

Abstract

The invention provides a construction method of a high-temperature-resistant liquid crystal polymer material gene pool, which is used for designing a liquid crystal polymer molecular structure. By collecting and sorting molecular structure data and performance parameters of the liquid crystal polymer, a database is established, and a performance prediction model is constructed by using a data mining and machine learning algorithm, so that rapid prediction of the performance of the liquid crystal polymer and optimal design of the molecular structure are realized. The method can shorten the research and development period, reduce the research and development cost, improve the accuracy and reliability of liquid crystal polymer performance prediction, optimize the molecular structure design, and improve the material performance and application value. The method is based on computer simulation and machine learning technologies, the performance of the liquid crystal polymer can be quickly predicted and optimized, and accurate design of a molecular structure is achieved. The method has high efficiency, accuracy and flexibility, and is suitable for research and development of liquid crystal polymer materials in different application scenes.

Description

Technical Field

[0001] The invention relates to the technical field of polymer materials, in particular to a method for designing the molecular structure of liquid crystal polymers and constructing a material gene library. Background Art

[0002] Liquid crystal polymers have shown broad application potential in aerospace, electronics, high-performance fibers, membrane materials and other fields due to their unique molecular arrangement and physical properties. However, the performance of liquid crystal polymers depends largely on their molecular structure, including chain length. Traditional molecular design methods rely on experimental trial and error, and have problems such as long R&D cycle, high cost and low efficiency. Therefore, developing an efficient and accurate liquid crystal polymer molecular structure design method is of great significance to promote the research and development and application of liquid crystal polymer materials. Summary of the invention

[0003] The present invention aims to provide a gene library of high temperature resistant liquid crystal polymer materials and a molecular structure design method, which is based on computer simulation and digital model technology, can quickly predict and optimize the performance of liquid crystal polymers and realize accurate design of molecular structures. The gene library contains a large amount of liquid crystal polymer molecular structure data and its corresponding performance parameters, realizing rapid prediction of liquid crystal polymer performance and optimal design of molecular structures.

[0004] The purpose of the present invention can be achieved by the following technical solutions:

[0005] A method for constructing a gene library of high temperature resistant liquid crystal polymer materials comprises the following steps:

[0006] (5) Establish two databases: liquid crystal polymer molecular structure and liquid crystal polymer performance;

[0007] (6) Testing the performance of liquid crystal polymers synthesized from a series of different polymerization monomers, obtaining the mapping relationship between different molecular structures and properties, and establishing a digital model;

[0008] (7) Verify the mapping relationship and impose boundary constraints on the digital model based on the known molecular structure and performance monitoring data of the liquid crystal polymer;

[0009] (8) Supplement the verified data into the mapping relationship and database to obtain a gene library of liquid crystal polymer molecular structure design materials.

[0010] As an embodiment, the method for constructing the above-mentioned high temperature resistant liquid crystal polymer material gene library specifically comprises the following steps:

[0011] (1) Setting the liquid crystal polymer monomer: an aromatic hydroxycarboxylic acid and several selected from aromatic hydroxylamines, aromatic diamines, aromatic dicarboxylic acids and aromatic diols;

[0012] (2) A part or all of the above aromatic hydroxycarboxylic acids, aromatic hydroxyamines, aromatic diamines, aromatic dicarboxylic acids, and aromatic diols may be independently polymerizable derivatives thereof;

[0013] (3) Examples of polymerizable derivatives of compounds having a hydroxyl group such as aromatic hydroxycarboxylic acids, aromatic hydroxyamines, aromatic diamines, and aromatic diols include acylated products obtained by acylation of the hydroxyl group to an acyloxy group.

[0014] In the combination of the above repeating units constituting the liquid crystal polymer:

[0015] The aromatic hydroxycarboxylic acid is selected from the repeating units of p-hydroxybenzoic acid and 6-hydroxy-2-naphthoic acid; the aromatic dicarboxylic acid is selected from the repeating units of terephthalic acid, isophthalic acid and 2,6-naphthalene dicarboxylic acid, preferably from the repeating units of terephthalic acid and isophthalic acid; the aromatic diol is selected from the repeating units of hydroquinone, 2,6-naphthalene diol and 4,4'-dihydroxybiphenyl, preferably from the repeating units of hydroquinone and 4,4'-dihydroxybiphenyl; the aromatic hydroxylamine is selected from the repeating units of p-aminophenol and p-aminonaphthol, preferably from the repeating units of p-aminophenol; the aromatic diamine is selected from the repeating units of p-phenylenediamine, 4,4'-biphenyl and 2,6-naphthalene diamine.

[0016] The liquid crystal polymers in this database contain at least one repeating unit of an aromatic hydroxycarboxylic acid.

[0017] Setting the ratio of each monomer in the liquid crystal polymer: According to different monomers and ratios, the performance mapping data of different liquid crystal polymers are obtained.

[0018] Setting the performance test standard of liquid crystal polymer: Perform DSC and rheology tests on each synthesized liquid crystal polymer to obtain the data of each liquid crystal polymer sample, and analyze the mapping relationship between the sample composition and the characterization performance to form a material characterization performance standard database.

[0019] Model verification and data expansion: The set liquid crystal polymer monomers and ratios, and the obtained multiple sets of mapping data of liquid crystal polymers are imported into the mapping model for verification. The machine learning method is used to make the model close to the test data of the embodiment. By setting new embodiment conditions and obtaining test data, the data applicable to the mapping model is expanded, and the constraints and boundaries of each component and ratio are determined.

[0020] The present invention establishes a gene library of high temperature resistant liquid crystal polymer molecular structure design materials, and realizes the prediction and optimization of liquid crystal polymer performance through data mining, machine learning, mapping model establishment and other technical means, which has important practical significance and scientific research value. The database of the components of the present invention can shorten the liquid crystal polymer research and development cycle and reduce research and development costs. Improve the accuracy and reliability of liquid crystal polymer performance prediction. Optimize the design of liquid crystal polymer molecular structure and improve material performance and application value. .

[0021] The beneficial effects of the present invention are:

[0022] 1. Through computer simulation and machine learning, the cycle of liquid crystal polymer molecular structure design is greatly shortened and R&D costs are reduced.

[0023] 2. Improve the accuracy and reliability of liquid crystal polymer performance prediction based on big data and machine learning models.

[0024] 3. According to different application requirements, the molecular structure design of liquid crystal polymer can be optimized, the molecular structure can be quickly adjusted and optimized, and the material performance and application value can be improved. DETAILED DESCRIPTION

[0025] The present invention is further described below by way of examples and comparative examples. Without violating the spirit of the present invention, the present invention should not be limited to the contents specifically shown in the following examples.

[0026] Product performance test method:

[0027] The present invention uses a differential scanning calorimeter (DSC 8000, PerkinElmer, USA) to test the melting point (T m ), and the test was performed according to ASTM D3418. The present invention uses a capillary rheometer (RH 2200, Malvern, UK) to test the melt viscosity (MV), and the test is performed according to ASTM D3835.

[0028] Example 1

[0029] Establish two databases: liquid crystal polymer molecular structure and liquid crystal polymer performance. Perform performance tests on liquid crystal polymers synthesized from a series of different polymerization monomers, obtain the mapping relationship between different molecular structures and performance, and establish a digital model; verify the mapping relationship based on known liquid crystal polymer molecular structure and performance monitoring data, and impose boundary constraints on the digital model; add the verified data to the mapping relationship and database to obtain a gene library of liquid crystal polymer molecular structure design materials.

[0030] p-Hydroxybenzoic acid and 6-hydroxy-2-naphthoic acid were selected as polymerization monomers.

[0031] The selected monomer ratio is as follows: 73 mol % of p-hydroxybenzoic acid and 27 mol % of 6-hydroxy-2-naphthoic acid.

[0032] The p-hydroxybenzoic acid, 6-hydroxy-2-naphthoic acid and acetic anhydride are reacted at a constant temperature of 120-130°C for 1 hour, then the temperature is raised to 185-195°C within 2 hours, and the temperature is further raised to 0.5-1 hour, and the acetylation reaction is completed; the acetate obtained by the acetylation reaction is then subjected to a melt polycondensation reaction, and the polymerization temperature is raised to a predetermined temperature within 3 hours to allow the polymerization reaction to proceed continuously; when the torque of the stirrer rises to a predetermined level, nitrogen is immediately introduced to terminate the polymerization reaction; the nitrogen pressure is increased to 2kg / cm 2 , release the liquid crystal polymer, and measure the melting point and melt viscosity of the obtained liquid crystal polymer.

[0033] Its melting point is about 280°C and its viscosity is about 55 Pa·s.

[0034] By analyzing the above experimental test results, a data mapping relationship between a set of polymerization monomer ratios and performance tests of this embodiment can be obtained, and its digital model can be obtained by summarizing, counting and generalizing.

[0035] By analogy, by using machine learning methods to analyze multiple groups of changes in monomer ratios and monomer types, we can obtain the data mapping relationship between multiple groups of preparations and monomer ratios and performance tests, verify the mapping relationship between the monomer ratio changes in the model and the performance test data, expand the digital model data, and complete the construction of the liquid crystal polymer gene library.

[0036] An application of a liquid crystal polymer gene library constructed by the aforementioned method comprises the following steps: the performance and characterization data of the liquid crystal polymer to be obtained are imported into a digital model of the liquid crystal polymer gene library, and the model uses a machine learning method to match the monomer types and proportions required for preparing the target liquid crystal polymer within constraints and boundaries: 70-80 mol % of p-hydroxybenzoic acid and 20-30 mol % of 6-hydroxy-2-naphthoic acid, and standard preparation process parameters are used as a recommended preparation scheme for the target liquid crystal polymer.

[0037] Example 2

[0038] The construction method and application of the liquid crystal polymer gene library provided in this embodiment are substantially the same as those in Example 1, except that:

[0039] Para-hydroxybenzoic acid, 6-hydroxy-2-naphthoic acid, hydroquinone and terephthalic acid were selected as polymerization monomers.

[0040] The selected monomer ratio is as follows: 42 mol% of p-hydroxybenzoic acid, 22 mol% of 6-hydroxy-2-naphthoic acid, 18 mol% of hydroquinone, and 18 mol% of terephthalic acid.

[0041] The p-hydroxybenzoic acid, 6-hydroxy-2-naphthoic acid, hydroquinone and acetic anhydride are reacted at a constant temperature of 120-130°C for 1 hour, then the temperature is raised to 185-195°C within 2 hours, and the temperature is further raised to 0.5-1 hour, and the acetylation reaction is completed; then the acetate obtained by the acetylation reaction is subjected to a melt polycondensation reaction with terephthalic acid, and the polymerization temperature is raised to a predetermined temperature within 3 hours to allow the polymerization reaction to proceed continuously; when the torque of the stirrer rises to a predetermined level, nitrogen is immediately introduced to terminate the polymerization reaction; and the nitrogen pressure is increased to 2 kg / cm 2 , release the liquid crystal polymer, name the obtained liquid crystal polymer and measure the melting point and melt viscosity.

[0042] Its melting point is about 340°C and its viscosity is about 28 Pa·s.

[0043] By analyzing the above experimental test results, a data mapping relationship between a set of polymerization monomer ratios and performance tests of this embodiment can be obtained, and its digital model can be obtained by summarizing, counting and generalizing.

[0044] By analogy, by using machine learning methods to analyze multiple groups of changes in monomer ratios and monomer types, we can obtain the data mapping relationship between multiple groups of preparations and monomer ratios and performance tests, verify the mapping relationship between the monomer ratio changes in the model and the performance test data, expand the digital model data, and complete the construction of the liquid crystal polymer gene library.

[0045] An application of a liquid crystal polymer gene library constructed by the aforementioned method comprises the following steps: importing the performance and characterization data of the liquid crystal polymer to be obtained into a digital model of the liquid crystal polymer gene library, and using a machine learning method within constraints and boundaries, the model matches the monomer types and proportions required for preparing the target liquid crystal polymer: 36-60 mol % of p-hydroxybenzoic acid, 16-24 mol % of 6-hydroxy-2-naphthoic acid, 12-20 mol % of hydroquinone, and 12-20 mol % of terephthalic acid, and using standard preparation process parameters as a recommended preparation scheme for the target liquid crystal polymer.

[0046] Example 3

[0047] The construction method and application of the liquid crystal polymer gene library provided in this embodiment are substantially the same as those in Example 1, except that:

[0048] Para-hydroxybenzoic acid, biphenol, terephthalic acid and isophthalic acid are selected as polymerization monomers.

[0049] The selected monomer ratio is as follows: 50 mol% of p-hydroxybenzoic acid, 20 mol% of biphenol, 18 mol% of terephthalic acid, and 12 mol% of isophthalic acid.

[0050] The p-hydroxybenzoic acid, biphenol and acetic anhydride are reacted at a constant temperature of 120-130°C for 1 hour, then the temperature is raised to 185-195°C within 2 hours, and the temperature is further raised to 0.5-1 hour, and the acetylation reaction is completed; then the acetate obtained by the acetylation reaction is subjected to melt polycondensation reaction with terephthalic acid and isophthalic acid, and the polymerization temperature is raised to a predetermined temperature within 3 hours to allow the polymerization reaction to proceed continuously; when the torque of the stirrer rises to a predetermined level, nitrogen is immediately introduced to terminate the polymerization reaction; the nitrogen pressure is increased to 2kg / cm 2 , release the liquid crystal polymer, name the obtained liquid crystal polymer and measure the melting point and melt viscosity.

[0051] Its melting point is about 350°C and its viscosity is about 45 Pa·s.

[0052] By analyzing the above experimental test results, a data mapping relationship between a set of polymerization monomer ratios and performance tests of this embodiment can be obtained, and its digital model can be obtained by summarizing, counting and generalizing.

[0053] By analogy, by using machine learning methods to analyze multiple groups of changes in monomer ratios and monomer types, we can obtain the data mapping relationship between multiple groups of preparations and monomer ratios and performance tests, verify the mapping relationship between the monomer ratio changes in the model and the performance test data, expand the digital model data, and complete the construction of the liquid crystal polymer gene library.

[0054] An application of a liquid crystal polymer gene library constructed by the above method comprises the following steps: importing the performance and characterization data of the liquid crystal polymer to be obtained into a digital model of the liquid crystal polymer gene library, and using a machine learning method within constraints and boundaries to match the monomer types and proportions required for preparing the target liquid crystal polymer: 40-60 mol % of p-hydroxybenzoic acid, 18-24 mol % of biphenol, 14-20 mol % of terephthalic acid, and 12-16 mol % of isophthalic acid, and using standard preparation process parameters as a recommended preparation plan for the target liquid crystal polymer.

[0055] Example 4

[0056] An application of the liquid crystal polymer gene library constructed by the above method is to import the characterization data of the target liquid crystal polymer to be obtained, the melting point is 370°C, the melt viscosity is 55Pa·s, into the digital type of the liquid crystal polymer gene library, and the model matches the polymerization monomer ratio required for preparing the target liquid crystal polymer: 60 mol% of p-hydroxybenzoic acid, 20 mol% of biphenol, 13 mol% of terephthalic acid, and 7 mol% of isophthalic acid. Standard preparation process parameters are used as the recommended preparation scheme for the target polymer flame-retardant composite material.

[0057] In the present invention, a gene library of liquid crystal polymer molecular structure design materials is constructed. The gene library greatly shortens the design cycle of liquid crystal polymer molecular structures through computer simulation and machine learning. Based on big data and machine learning models, the performance of liquid crystal polymers can be accurately predicted; and the molecular structure can be quickly adjusted and optimized according to different application requirements.

Claims

1. A method for constructing a gene library of high temperature resistant liquid crystal polymer materials, characterized in that: The following steps are involved: (1) Establish two databases: liquid crystal polymer molecular structure and liquid crystal polymer performance; (2) Testing the performance of liquid crystal polymers synthesized from a series of different polymerization monomers, obtaining the mapping relationship between different molecular structures and properties, and establishing a digital model; (3) Based on the known molecular structure and performance monitoring data of liquid crystal polymers, the mapping relationship is verified and the boundary constraints of the digital model are imposed; (4) Supplement the verified data into the mapping relationship and database to obtain a gene library of liquid crystal polymer molecular structure design materials.

2. The method for constructing a high temperature resistant liquid crystal polymer material gene library according to claim 1, characterized in that: The liquid crystal polymer monomer is set to be an aromatic hydroxycarboxylic acid and several selected from aromatic hydroxylamines, aromatic diamines, aromatic dicarboxylic acids and aromatic diols; Part or all of the above aromatic hydroxycarboxylic acids, aromatic hydroxyamines, aromatic diamines, aromatic dicarboxylic acids, and aromatic diols may be independently polymerizable derivatives thereof; Examples of polymerizable derivatives of compounds having a hydroxyl group such as aromatic hydroxycarboxylic acids, aromatic hydroxyamines, aromatic diamines, and aromatic diols include acylated products obtained by acylation of the hydroxyl group and conversion of the hydroxyl group to an acyloxy group.

3. The method for constructing a high temperature resistant liquid crystal polymer material gene library according to claim 2, characterized in that: In the combination of the above repeating units constituting the liquid crystal polymer: The aromatic hydroxycarboxylic acid is selected from the repeating units of p-hydroxybenzoic acid and 6-hydroxy-2-naphthoic acid; the aromatic dicarboxylic acid is selected from the repeating units of terephthalic acid, isophthalic acid and 2,6-naphthalenedicarboxylic acid; the aromatic diol is selected from the repeating units of hydroquinone, 2,6-naphthalenediol and 4,4'-dihydroxybiphenyl; the aromatic hydroxylamine is selected from the repeating units of p-aminophenol and p-aminonaphthol; the aromatic diamine is selected from the repeating units of p-phenylenediamine, 4,4'-biphenyl and 2,6-naphthalenediamine.

4. The method for constructing a high temperature resistant liquid crystal polymer material gene library according to claim 3, characterized in that: In the combination of the above repeating units constituting the liquid crystal polymer: The aromatic hydroxycarboxylic acid is selected from the repeating units of terephthalic acid and isophthalic acid; the aromatic diol is selected from the repeating units of hydroquinone and 4,4'-dihydroxybiphenyl; and the aromatic hydroxylamine is selected from the repeating units of p-aminophenol.

5. The method for constructing a high temperature resistant liquid crystal polymer material gene library according to claim 1, characterized in that: Setting the ratio of each monomer in the liquid crystal polymer: According to different monomers and ratios, the performance mapping data of different liquid crystal polymers are obtained. Setting the performance test standard of liquid crystal polymer: Perform DSC and rheology tests on each synthesized liquid crystal polymer to obtain the data of each liquid crystal polymer sample, and analyze the mapping relationship between the sample composition and the characterization performance to form a material characterization performance standard database. Model verification and data expansion: The set liquid crystal polymer monomers and ratios, and the obtained multiple sets of mapping data of liquid crystal polymers are imported into the mapping model for verification. The machine learning method is used to make the model close to the test data of the embodiment. By setting new embodiment conditions and obtaining test data, the data applicable to the mapping model is expanded, and the constraints and boundaries of each component and ratio are determined.