Asphalt saturated fraction representative molecule selection method and system based on statistical analysis, and asphalt molecule model
Through quantum chemistry calculation and statistical analysis, representative molecules of asphalt saturated parts were selected, which solved the problem of lack of objective argumentation and high time cost in the establishment of asphalt molecular models in the existing technology, and achieved efficient and accurate construction of asphalt molecular models, which was suitable for different Asphalt system in the project.
Patent Information
- Application Number
- CN202411254878.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-09
- Publication Date
- 2024-12-13
AI Technical Summary
The establishment of asphalt saturated molecular model in the prior art lacks objective argumentation, and the selection criteria are relatively subjective, which makes it difficult to guarantee the accuracy of modeling and high time cost, so it is impossible to select suitable representative molecules for the actual asphalt system in different projects.
Using methods based on quantum chemistry calculation and statistical analysis, a variety of asphalt saturated molecules are collected, and the stable molecular configuration with the lowest energy is constructed, molecular morphology and electronic properties are calculated. Representative molecules are selected through principal component analysis and systematic clustering. , and combine H/C ratio and other characteristics to comprehensively determine representative molecules.
It realizes saving time and cost while ensuring the accuracy of the model, quickly identifying and applying the most suitable representative molecules of asphalt saturated parts, meeting the complex characteristics of different asphalt samples, and improving the accuracy of selection of representative molecules and simplifying modeling.
Smart Images
Figure CN119132427A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the technical field of asphalt simulation, and relates to a method for selecting representative molecules of asphalt saturated fraction based on quantum chemical calculation and statistical analysis, and in particular to a method and system for selecting representative molecules of asphalt saturated fraction based on quantum chemical calculation and statistical analysis, and an asphalt molecular model. Background Art
[0002] The saturated fraction is the most chemically stable component among the four components of asphalt. Its content and type have an important influence on the stability, viscosity, aging resistance and low-temperature performance of asphalt. In order to deeply study the performance of asphalt and clarify the reaction mechanism of asphalt, it is necessary to study the saturated fraction molecules of asphalt at the nanoscopic level. Although more and more studies have selected asphalt saturated fraction molecular models, the selection criteria are usually subjective, and the selection of saturated fraction molecules when establishing asphalt molecular models lacks objective evidence. However, considering the time cost and actual situation, it is unreasonable to add all saturated fraction molecules to the model in related studies. Therefore, in order to take into account the accuracy of modeling and save time cost, it is necessary to select corresponding saturated fraction representative molecules for the actual asphalt system in different projects. Summary of the invention
[0003] In view of the deficiencies in the prior art, the present invention provides a method and system for selecting representative molecules of asphalt saturated fraction based on statistical analysis, and an asphalt molecular model. In practical applications, while ensuring the accuracy of the asphalt molecular model, it saves time cost and reduces the difficulty of modeling, and selects corresponding representative molecules of saturated fraction for the actual asphalt system in the project.
[0004] To achieve the above object, the present invention adopts the following technical solutions:
[0005] A method for selecting representative molecules of asphalt saturated fraction based on statistical analysis: collecting a variety of asphalt saturated fraction molecules; constructing the lowest energy stable molecular configuration of each molecule; calculating the molecular morphology index and electronic property index of each stable molecular configuration; drawing scatter matrix diagrams and correlation coefficient diagrams of multiple specific molecular morphology indexes and electronic property indexes, and obtaining representative molecules selected based on molecular morphology and electronic property through principal component analysis and system clustering; comprehensively analyzing the characteristics of each representative molecule in molecular morphology index and electronic property index and the differences between molecules, to obtain a method for selecting representative molecules of asphalt saturated fraction.
[0006] To optimize the above technical solutions, the specific measures taken also include:
[0007] Further, the following steps are included:
[0008] S1. Collect various asphalt saturated fractions;
[0009] S2. Establish a three-dimensional model of each molecule according to the structural formula; perform geometric optimization on each three-dimensional model to obtain a stable molecular configuration with the lowest energy;
[0010] S3, calculating the molecular morphology index and electronic property index of the stable molecular configuration of each molecule through Multiwfn;
[0011] S4. Select six molecular morphology indices, including molecular weight (obtained by calculating the molecular formula), van der Waals volume (obtained by the Marching Tetrahedron algorithm, where the electron density isosurface is 0.001 au), density (obtained by converting van der Waals volume and molecular weight), van der Waals surface area (obtained by the Marching Tetrahedron algorithm, where the electron density isosurface is 0.001 au), SDP (the maximum value of the atom in the molecule deviating from the molecular plane) and MPP (the root mean square deviation of each atom from the fitting plane), draw scatter matrix diagrams and correlation coefficient diagrams of the six indices, and analyze the correlation relationship between the indices; obtain representative molecules selected based on molecular morphology through principal component analysis and systematic clustering;
[0012] Four electronic property indicators were selected, including saturated dipole moment (calculated by Hirshfeld weight function using Multiwfn software), MPI (mean of absolute value of molecular surface electrostatic potential), Pi (average deviation of molecular surface electrostatic potential), and HOMO-LUMO energy gap (energy level difference between the highest occupied molecular orbital and the lowest unoccupied molecular orbital, calculated using Multiwfn software). Scatter matrix diagrams and correlation coefficient diagrams of the four indicators were drawn to analyze the correlation between the indicators. Representative molecules selected based on electronic properties were obtained through principal component analysis and systematic clustering, combined with the H / C (ratio of the number of H atoms to C atoms in a molecule, calculated based on the molecular formula) of saturated molecular asphalt.
[0013] S5. Combining the characteristics of each representative molecule in terms of molecular morphology and electronic properties and the differences between molecules, a method for selecting representative molecules for asphalt saturation fraction is obtained.
[0014] Furthermore, in S2, the calculation method used for the geometry optimization is density functional theory, the functional is B3LYP, and the basis set is 6-31G(d,p).
[0015] Furthermore, in S4, the specific process of obtaining representative molecules selected based on molecular morphology is as follows: performing Z-Score standardization on the data of the six molecular morphology indicators, and using principal component analysis to reduce the dimensions of the six indicators and convert them into independent indicators, calculating the eigenvectors of the principal components of each indicator, calculating the scoring functions of the first three principal components based on the eigenvectors, using the scoring function values of the first three principal components as Euclidean space coordinates, calculating the Euclidean distances of various asphalt saturated molecules, and drawing a systematic clustering diagram of various asphalt saturated molecules; obtaining representative molecules selected based on molecular morphology according to the systematic clustering diagram; obtaining. The specific process of selecting representative molecules based on electronic properties is as follows: Z-Score standardization is performed on the data of the four electronic property indicators, and principal component analysis is used to reduce the dimension of the four indicators and convert them into independent indicators. The eigenvectors of the principal components of each indicator are calculated, and the scoring functions of the first two principal components are calculated based on the eigenvectors. The scoring function values of the first two principal components are used as Euclidean space coordinates to calculate the Euclidean distances of various asphalt saturated molecules and draw a systematic clustering diagram of various asphalt saturated molecules; representative molecules selected based on electronic properties are obtained based on the systematic clustering diagram and combined with the H / C of the asphalt saturated molecules.
[0016] Furthermore, the asphalt saturated fractions are S1, C 30 H 62 ; S2, C 28 H 58 ; S3, C 22 H 42 ; S4, C 35 H 62 ; S5, C 36 H 70 ; S6, C 37 H 72 ; S7, C 29 H 60 ; S8, C 51 H 94 ; S9, C 22 H 46 .
[0017] Furthermore, in the molecular morphology index, the scoring function of the first three principal components is:
[0018] sPC1=0.53A+0.50B+0.41C+0.31D+0.33E+0.32F;
[0019] sPC2=-0.21A-0.30B+0.22C-0.52D+0.51E+0.53F;
[0020] sPC3=-0.11A+0.06B-0.78C+0.37D+0.36E+0.34F;
[0021] Where sPC1 is the first principal component, sPC2 is the second principal component, sPC3 is the third principal component, and A to F represent the molecular weight, van der Waals volume, density, van der Waals surface area, SDP, and MPP of each asphalt saturated fraction after standardization, respectively;
[0022] The representative molecules selected based on molecular morphology are S2, S8, S3, S9 or S4; the selection method is: when the sample molecule has more than 3 branches, the representative molecule is S2; when the sample molecular weight is greater than 600g / mol, the representative molecule is S8; when the sample molecular weight is less than 400g / mol and contains branches and carbon rings, the representative molecule is S3; when the sample molecular weight is less than 400g / mol and does not contain branches and carbon rings, the representative molecule is S9; when the sample molecular weight is greater than 400g / mol and less than 600g / mol and the molecular density is greater than 1.10g / cm3, the representative molecule is S4;
[0023] Among the electronic property indicators, the scoring functions of the first two principal components are:
[0024] ePC1=0.41G+0.53H+0.51I-0.52J;
[0025] ePC2=-0.71G+0.40H+0.48I+0.31J;
[0026] Where, ePC1 is the first principal component, ePC2 is the second principal component, ePC3 is the third principal component, and G~J represent the dipole moment, MPI, PI and HOMO-LUMO energy gap of each saturated molecular molecule after standardization;
[0027] The representative molecules selected based on molecular morphology are S2, S3, S4, S9 or S5; the selection method is: when the sample molecule does not contain a carbon ring and has more than 3 branches, the representative molecule is S2; when the sample molecule contains less than 3 carbon rings and has more than 3 branches, the representative molecule is S3; when the sample molecule contains more than 3 carbon rings and H / C is less than 2.0, the representative molecule is S4; when the sample molecule has an alkane chain of more than 15 carbon atoms and does not contain a carbon ring, the representative molecule is S9; when the sample molecule has an alkane chain of more than 15 carbon atoms and contains a carbon ring, the representative molecule is S5.
[0028] Furthermore, the method for selecting representative molecules of the asphalt saturated fraction is as follows: if the sample molecule does not contain a carbon ring and has more than 3 branches, S2 is selected as the representative molecule; if the sample molecule contains less than 3 carbon rings and has more than 3 branches, S3 is selected as the representative molecule; if the sample molecule contains more than 3 carbon rings, H / C is less than 2.0, and the molecular weight is less than 600g / mol, S4 is selected as the representative molecule; if the sample molecule contains more than 3 carbon rings, H / C is less than 2.0, and the molecular weight is greater than 600g / mol, S8 is selected as the representative molecule; if the sample molecule has an alkane chain of more than 15 carbon atoms and contains a carbon ring, S5 is selected as the representative molecule; if the sample molecule has an alkane chain of more than 15 carbon atoms and no carbon ring, S9 is selected as the representative molecule.
[0029] The present invention also provides a representative molecule selection system for asphalt saturated fraction, which is used to execute the above-mentioned selection method, including: a search unit, which is used to collect a variety of asphalt saturated fraction molecules; a modeling unit, which is used to construct the lowest energy stable molecular configuration of each molecule; a calculation and analysis unit, which is used to calculate the molecular morphology index and electronic property index of each stable molecular configuration; respectively draw scatter matrix diagrams and correlation coefficient diagrams of multiple specific molecular morphology indexes and electronic property indexes, and obtain representative molecules selected based on molecular morphology and electronic property through principal component analysis and system clustering; a processing unit, which is used to comprehensively analyze the characteristics of each representative molecule in molecular morphology index and electronic property index and the differences between molecules, and obtain a method for selecting representative molecules of asphalt saturated fraction.
[0030] The present invention also provides a method for establishing an asphalt molecular model: performing component and element tests on an asphalt sample, selecting representative molecules of the saturated fraction of the asphalt sample based on the test results and the above-mentioned selection method, and then using the representative molecules of the saturated fraction to establish an asphalt molecular model.
[0031] The present invention also provides an asphalt molecular model, which is established using the above method.
[0032] The beneficial effects of the present invention are as follows: based on the stable molecular configuration, the present invention performs statistical analysis on multiple specific variables contained in the molecular morphology index and the electronic property index, and comprehensively determines the selection method of the representative molecules of the asphalt saturation group through principal component analysis and system clustering methods. The method of the present invention can efficiently select suitable representative molecules of the asphalt saturation fraction according to the test results, and provides an effective reference for selecting suitable representative molecules of the saturation fraction according to actual engineering data to solve practical problems. Specifically, the present invention customizes molecular modeling according to actual conditions, quickly and accurately identifies and applies the most suitable representative molecules of the saturation fraction to meet the complex characteristics of different asphalt samples; saves time and cost, simplifies model construction, and takes into account the accuracy of modeling; analyzes the nanoscopic characteristics of the saturation fraction, and deeply analyzes the molecular morphology and electronic property indicators of the saturation fraction; integrates experimental data with theoretical calculations, and proposes a strategy for adjusting representative molecules for engineering projects with experimental data, further improving the accuracy of representative molecule selection. BRIEF DESCRIPTION OF THE DRAWINGS
[0033] Figure 1 It is the molecular structure formula of the asphalt saturated fraction collected in the present invention;
[0034] Figure 2a It is a scatter matrix diagram and correlation coefficient diagram of the saturation fraction morphological index drawn in the present invention;
[0035] Figure 2b It is a scatter matrix diagram and correlation coefficient diagram of the saturated electronic property index drawn in the present invention;
[0036] Figure 3a is a principal component score graph of the saturation fraction morphological index calculated in the present invention;
[0037] Figure 3b is a principal component score diagram of the saturated electronic property index calculated in the present invention;
[0038] Figure 4a is a systematic cluster diagram of the saturation fraction morphological index calculated in the present invention;
[0039] Figure 4b is a systematic cluster diagram of the saturated sub-electronic property index calculated in the present invention;
[0040] Figure 5 It is a representative molecular diagram of saturation fraction suitable for constructing asphalt molecular model according to different requirements of molecular simulation in the present invention. DETAILED DESCRIPTION
[0041] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments.
[0042] This embodiment provides a method for selecting representative molecules of asphalt saturation fraction based on statistical analysis, comprising the following steps:
[0043] S1. Consult literature and databases to collect 9 asphalt saturation molecules: S1, C 30 H 62 ; S2, C 28 H 58 ; S3, C 22 H 42 ; S4, C 35 H 62 ; S5, C 36 H 70 ; S6, C 37 H 72 ; S7, C 29 H 60 ; S8, C 51 H 94 ; S9, C 22 H 46 , the structural formula is Figure 1 The collected asphalt saturated molecules come from asphalt molecules classified based on SARA components in the literature, as well as molecules considered as saturated components in various crude oil asphalt raw material component determination tests.
[0044] S2. Build a three-dimensional model of each asphalt saturated molecular structure based on the structural formula. Use Gaussian 09 software to perform geometric optimization on each three-dimensional model to obtain the stable molecular configuration with the lowest energy. The calculation method used for geometric optimization is density functional theory, B3LYP is selected as the functional, and 6-31G (d, p) is selected as the basis set.
[0045] S3. Calculate the molecular morphology index and electronic property index of the stable molecular configuration of each molecule through Multiwfn software.
[0046] S4. The saturated molecules were studied from the perspective of molecular morphology indicators, and six indicators including molecular weight, van der Waals volume, density, van der Waals surface area, SDP and MPP were selected for analysis. The molecular weight was obtained by calculating the molecular formula, and the van der Waals volume and van der Waals surface area were obtained by the Marching Tetrahedron algorithm, where the electron density isosurface was taken as 0.001 au; the density was converted based on the van der Waals volume and molecular weight; MPP refers to the root mean square deviation of each atom from the fitting plane, and SDP refers to the maximum value of the atom in the molecule deviating from the molecular plane.
[0047] Draw a scatter matrix diagram and Pearson correlation coefficient diagram of each indicator to explore the correlation relationship between the indicators, such as Figure 2a shown.
[0048] The data of the six molecular morphology indicators were standardized by Z-Score, and the six indicators were reduced in dimension by principal component analysis to transform them into independent indicators. The principal component analysis results of the saturated molecular morphology indicators after Z-Score standardization are shown in Table 1.
[0049] Table 1 Results of principal component analysis of saturated molecular morphological indices
[0050] principal component Eigenvalue Variance percentage (%) Cumulative variance percentage (%) sPC1 3.22 53.68 53.68 sPC2 2.15 35.80 89.48 sPC3 0.59 9.78 99.26 sPC4 0.03 0.49 99.75 sPC5 0.01 0.24 99.99 sPC6 <![CDATA[7.19×10 -5 ]]> 0.001 100.00
[0051] Calculate the eigenvector of the principal component of each indicator, and calculate the scoring function of the first three principal components based on the eigenvector:
[0052] sPC1=0.53A+0.50B+0.41C+0.31D+0.33E+0.32F
[0053] sPC2=-0.21A-0.30B+0.22C-0.52D+0.51E+0.53F
[0054] sPC3=-0.11A+0.06B-0.78C+0.37D+0.36E+0.34F
[0055] Where sPC1 is the first principal component, sPC2 is the second principal component, sPC3 is the third principal component, and A to F represent the molecular weight, van der Waals volume, density, van der Waals surface area, SDP, and MPP of each saturated fraction after standardization, respectively.
[0056] The scoring function values of the first three principal components are used as the Euclidean space coordinates (the scores of the first three principal components of each saturation score are shown in the figure below) Figure 3a As shown), the Euclidean distances of the 9 saturated molecular molecules are calculated, and the systematic clustering diagrams of the 9 saturated molecular molecules are drawn, as shown in Figure 4a shown.
[0057] In the system clustering diagram, the larger the Euclidean distance of the initial classification of the asphalt saturation score, the greater the difference between it and other asphalt saturation scores. According to the system clustering diagram, the corresponding representative molecule selection scheme is obtained: if the experiment determines that the molecule has more than 3 branches, S2 is selected as the representative molecule; if the experiment determines that the molecular weight is greater than 600g / mol, S8 is selected as the representative molecule; if the experiment determines that the molecular weight is less than 400g / mol and contains branches and carbon rings, S3 is selected as the representative molecule; if the experiment determines that the molecular weight is less than 400g / mol and does not contain branches and carbon rings, S9 is selected as the representative molecule; if the experiment determines that the molecular weight is greater than 400g / mol and less than 600g / mol and the molecular density is greater than 1.10g / cm 3 , S4 was selected as the representative molecule.
[0058] The saturated molecules were studied from the perspective of electronic properties, and four indicators, namely, saturated dipole moment, MPI, Pi, and HOMO-LUMO energy gap, were selected for analysis. The dipole moment was calculated using Multiwfn software through the Hirshfeld weight function; MPI is the mean of the absolute value of the molecular surface electrostatic potential; Pi is the average deviation of the molecular surface electrostatic potential; and the HOMO-LUMO energy gap is the energy level difference between the highest occupied molecular orbital and the lowest unoccupied molecular orbital, calculated using Multiwfn software.
[0059] Draw a scatter matrix diagram and Pearson correlation coefficient diagram of the four indicators to explore the correlation between the indicators, such as Figure 2b shown.
[0060] The data of the four electronic property indicators were standardized by Z-Score, and the principal component analysis was used to reduce the dimension of the four indicators and transform them into independent indicators. The principal component analysis results of the saturated electronic property indicators after Z-Score standardization are shown in 2.
[0061] Table 2 Results of principal component analysis of saturated electronic property indicators
[0062] principal component Eigenvalue Variance percentage (%) Cumulative variance percentage (%) PC1 3.02 75.59 75.59 PC2 0.83 20.77 96.36 PC3 0.14 3.57 99.92 PC4 0.00 0.08 100.00
[0063] Calculate the eigenvector of the principal component of each indicator, and calculate the scoring function of the first two principal components based on the eigenvector:
[0064] ePC1=0.41G+0.53H+0.51I-0.52J
[0065] ePC2=-0.71G+0.40H+0.48I+0.31J
[0066] Where ePC1 is the first principal component, ePC2 is the second principal component, ePC3 is the third principal component, and G~J represent the dipole moment, MPI, PI and HOMO-LUMO energy gap of each saturated molecule after standardization.
[0067] The scoring function values of the first two principal components are used as the Euclidean space coordinates (the scores of the first two principal components of each saturation score are shown in the figure below) Figure 3b As shown), the Euclidean distances of the 9 saturated molecular molecules are calculated, and the systematic clustering diagrams of the 9 saturated molecular molecules are drawn, as shown in Figure 4b shown.
[0068] The molecular H / C values of the nine saturated fractions were calculated and the results are shown in Table 3.
[0069] Table 3 Saturated molecular H / C atom number ratio
[0070] Molecular number Molecular formula H / C general formula S1 <![CDATA[C 30 H 62 ]]> 2.07 <![CDATA[C n H 2n+2 ]]> S2 <![CDATA[C 28 H 58 ]]> 2.07 <![CDATA[C n H 2n+2 ]]> S3 <![CDATA[C 22 H 42 ]]> 1.91 <![CDATA[C n H 2n-2 ]]> S4 <![CDATA[C 35 H 62 ]]> 1.77 <![CDATA[C n H 2n-8 ]]> S5 <![CDATA[C 36 H 70 ]]> 1.94 <![CDATA[C n H 2n-2 ]]> S6 <![CDATA[C 37 H 72 ]]> 1.95 <![CDATA[C n H 2n-2 ]]> S7 <![CDATA[C 29 H 60 ]]> 2.07 <![CDATA[C n H 2n+2 ]]> S8 <![CDATA[C 51 H 94 ]]> 1.84 <![CDATA[C n H 2n-8 ]]> S9 <![CDATA[C 22 H 46 ]]> 2.09 <![CDATA[C n H 2n+2 ]]>
[0071] According to the system cluster diagram and combined with the H / C values of 9 saturated molecular weights, the corresponding representative molecule selection scheme is derived: if the experiment determines that the molecule does not contain a carbon ring and has more than 3 branches, S2 is selected as the representative molecule; if the experiment determines that the molecule contains less than 3 carbon rings and has more than 3 branches, S3 is selected as the representative molecule; if the experiment determines that the molecule contains more than 3 carbon rings, that is, H / C is less than 2.0, S4 is selected as the representative molecule; if the experiment determines that the molecule has an alkane chain of more than 15 carbon atoms and does not contain a carbon ring, S9 is selected as the representative molecule; if the experiment determines that the molecule has an alkane chain of more than 15 carbon atoms and contains a carbon ring, S5 is selected as the representative molecule.
[0072] S5. Based on the characteristics and intermolecular differences of each representative molecule in terms of molecular morphology and electronic properties, a method for selecting representative molecules for asphalt saturation fraction is obtained, such as Figure 5 As shown: if the sample molecule does not contain a carbon ring and has more than 3 side chains, S2 is selected as the representative molecule; if the sample molecule contains less than 3 carbon rings and has more than 3 side chains, S3 is selected as the representative molecule; if the sample molecule contains more than 3 carbon rings, H / C is less than 2.0, and the molecular weight is less than 600g / mol, S4 is selected as the representative molecule; if the sample molecule contains more than 3 carbon rings, H / C is less than 2.0, and the molecular weight is greater than 600g / mol, S8 is selected as the representative molecule; if the sample molecule has an alkane chain of more than 15 carbon atoms and contains a carbon ring, S5 is selected as the representative molecule; if the sample molecule has an alkane chain of more than 15 carbon atoms and no carbon ring, S9 is selected as the representative molecule.
[0073] The present embodiment also provides a representative molecule selection system for asphalt saturated fraction, which is used to execute the above-mentioned selection method, including: a search unit, which is used to collect a variety of asphalt saturated fraction molecules; a modeling unit, which is used to construct the lowest energy stable molecular configuration of each molecule; a calculation and analysis unit, which is used to calculate the molecular morphology index and electronic property index of each stable molecular configuration; respectively draw scatter matrix diagrams and correlation coefficient diagrams of multiple specific molecular morphology indexes and electronic property indexes, and obtain representative molecules selected based on molecular morphology and electronic property through principal component analysis and system clustering; a processing unit, which is used to comprehensively analyze the characteristics of each representative molecule in molecular morphology index and electronic property index and the differences between molecules, and obtain a method for selecting representative molecules of asphalt saturated fraction.
[0074] This embodiment also provides an asphalt molecular model, and its establishment method is: perform component and element tests on asphalt samples. Specifically, it includes: gel chromatography test analysis to determine molecular weight, elemental analysis test to determine H / C, infrared absorption spectrum and ultraviolet absorption spectrum, nuclear magnetic resonance spectrum, mass spectrometry structure analysis and other test results are combined to determine the chemical structure, that is, including carbon chain information. Then, based on the test results and the above-mentioned selection method, the representative molecule of the saturated fraction of the asphalt sample is selected, and then the asphalt molecular model is established using the representative molecule of the saturated fraction.
[0075] In the present invention, unless otherwise specified, the scientific and technical terms used herein have the meanings commonly understood by those skilled in the art. In addition, the reagents, materials and operating procedures used herein are reagents, materials and conventional procedures widely used in the corresponding fields.
[0076] It should be noted that the terms such as "upper", "lower", "left", "right", "front", "back", etc. cited in the invention are only for the convenience of description and are not used to limit the scope of implementation of the present invention. Changes or adjustments in their relative relationships should be regarded as the scope of implementation of the present invention without substantially changing the technical content.
[0077] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.
Claims
1. A method for selecting representative molecules of asphalt saturation fraction based on statistical analysis, characterized in that: Collect a variety of asphalt saturated fraction molecules; construct the lowest energy stable molecular configuration of each molecule; calculate the molecular morphology index and electronic property index of each stable molecular configuration; draw scatter matrix diagrams and correlation coefficient diagrams of multiple specific molecular morphology indexes and electronic property indexes, and obtain representative molecules selected based on molecular morphology and electronic property through principal component analysis and system clustering; comprehensively analyze the characteristics of each representative molecule in molecular morphology index and electronic property index and the differences between molecules, and obtain a method for selecting representative molecules of asphalt saturated fraction.
2. The method for selecting representative molecules of asphalt saturation fraction based on statistical analysis according to claim 1, characterized in that: The following steps are involved: S1. Collect various asphalt saturated fractions; S2. Establish a three-dimensional model of each molecule according to the structural formula; perform geometric optimization on each three-dimensional model to obtain a stable molecular configuration with the lowest energy; S3, calculating the molecular morphology index and electronic property index of the stable molecular configuration of each molecule through Multiwfn; S4. Select six molecular morphology indicators, namely molecular weight, van der Waals volume, density, van der Waals surface area, SDP and MPP, draw scatter matrix diagrams and correlation coefficient diagrams of the six indicators, and analyze the correlation relationship between the indicators; obtain representative molecules selected based on molecular morphology through principal component analysis and systematic clustering; Four electronic property indicators, namely saturated dipole moment, MPI, Pi, and HOMO-LUMO energy gap, were selected to draw scatter matrix diagrams and correlation coefficient diagrams of the four indicators, and to analyze the correlation between the indicators; representative molecules selected based on electronic properties were obtained through principal component analysis and systematic clustering, combined with the H / C of the saturated molecules of asphalt; S5. Combining the characteristics of each representative molecule in terms of molecular morphology and electronic properties and the differences between molecules, a method for selecting representative molecules for asphalt saturation fraction is obtained.
3. The method for selecting representative molecules of asphalt saturation fraction based on statistical analysis according to claim 2, characterized in that: In S2, the calculation method used for the geometry optimization is density functional theory, the functional is B3LYP, and the basis set is 6-31G(d,p).
4. The method for selecting representative molecules of asphalt saturation fraction based on statistical analysis according to claim 2, characterized in that: In S4, the specific process of obtaining representative molecules selected based on molecular morphology is as follows: Z-Score standardization is performed on the data of the six molecular morphology indicators, and the six indicators are reduced in dimension by principal component analysis to convert them into independent indicators, and the characteristic vectors of the principal components of each indicator are calculated, and the scoring functions of the first three principal components are calculated according to the characteristic vectors, and the scoring function values of the first three principal components are used as Euclidean space coordinates to calculate the Euclidean distances of various asphalt saturated molecules, and a systematic clustering diagram of various asphalt saturated molecules is drawn; representative molecules selected based on molecular morphology are obtained according to the systematic clustering diagram; The specific process of obtaining the representative molecules selected based on electronic properties is as follows: Z-Score standardization is performed on the data of the four electronic property indicators, and principal component analysis is used to reduce the dimension of the four indicators and convert them into independent indicators, and the principal component eigenvectors of each indicator are calculated. The scoring function of the first two principal components is calculated based on the eigenvectors, and the scoring function values of the first two principal components are used as Euclidean space coordinates to calculate the Euclidean distances of various asphalt saturated molecules and draw a systematic clustering diagram of various asphalt saturated molecules; based on the systematic clustering diagram and combined with the H / C of the asphalt saturated molecules, the representative molecules selected based on electronic properties are obtained.
5. The method for selecting representative molecules of asphalt saturation fraction based on statistical analysis according to claim 3 is characterized by: The asphalt saturation molecules are S1, C 30 H 62 ; S2, C 28 H 58 ; S3, C 22 H 42 ; S4, C 35 H 62 ; S5, C 36 H 70 ; S6, C 37 H 72 ; S7, C 29 H 60 ; S8, C 51 H 94 ; S9, C 22 H 46 .
6. The method for selecting representative molecules of asphalt saturation fraction based on statistical analysis according to claim 5, characterized in that: In the molecular morphology index, the scoring function of the first three principal components is: sPC1=0.53A+0.50B+0.41C+0.31D+0.33E+0.32F; sPC2=-0.21A-0.30B+0.22C-0.52D+0.51E+0.53F; sPC3=-0.11A+0.06B-0.78C+0.37D+0.36E+0.34F; Where sPC1 is the first principal component, sPC2 is the second principal component, sPC3 is the third principal component, and A to F represent the molecular weight, van der Waals volume, density, van der Waals surface area, SDP, and MPP of each asphalt saturated fraction after standardization, respectively; Among the electronic property indicators, the scoring functions of the first two principal components are: ePC1=0.41G+0.53H+0.51I-0.52J; ePC2=-0.71G+0.40H+0.48I+0.31J; Where ePC1 is the first principal component, ePC2 is the second principal component, ePC3 is the third principal component, and G~J represent the dipole moment, MPI, PI and HOMO-LUMO energy gap of each saturated molecule after standardization, respectively.
7. The method for selecting representative molecules of asphalt saturation fraction based on statistical analysis according to claim 6, characterized in that: The method for selecting representative molecules of asphalt saturated fraction is as follows: if the sample molecule does not contain a carbon ring and has more than 3 branches, S2 is selected as the representative molecule; if the sample molecule contains less than 3 carbon rings and has more than 3 branches, S3 is selected as the representative molecule; if the sample molecule contains more than 3 carbon rings, H / C is less than 2.0, and the molecular weight is less than 600g / mol, S4 is selected as the representative molecule; if the sample molecule contains more than 3 carbon rings, H / C is less than 2.0, and the molecular weight is greater than 600g / mol, S8 is selected as the representative molecule; if the sample molecule has an alkane chain of more than 15 carbon atoms and contains a carbon ring, S5 is selected as the representative molecule; if the sample molecule has an alkane chain of more than 15 carbon atoms and no carbon ring, S9 is selected as the representative molecule.
8. A system for selecting representative molecules of asphalt saturation fraction, characterized by: Used to perform the selection method according to any one of claims 1 to 7, comprising: Search unit, used to collect various asphalt saturated fractions; Modeling unit, used to construct the lowest energy stable molecular configuration of each molecule; A calculation and analysis unit is used to calculate the molecular morphology index and electronic property index of each stable molecular configuration; draw scatter matrix diagrams and correlation coefficient diagrams of multiple specific molecular morphology indexes and electronic property indexes, and obtain representative molecules selected based on molecular morphology and electronic property through principal component analysis and system clustering; The processing unit is used to comprehensively analyze the characteristics and intermolecular differences of each representative molecule in terms of molecular morphology index and electronic property index to obtain a method for selecting representative molecules of asphalt saturation fraction.
9. A method for establishing an asphalt molecular model, characterized in that: Conduct component and element tests on the asphalt sample, select representative molecules of the saturated fraction of the asphalt sample based on the test results and the selection method as described in any one of claims 1 to 7, and then use the representative molecules of the saturated fraction to establish an asphalt molecular model.
10. A molecular model of asphalt, characterized in that: The method according to claim 9 is used to establish.