Analysis method for determining influence on ionization energy and electron affinity of triglyceride molecules
By constructing and analyzing the molecular descriptor feature quantity of natural ester and calculating its ionization energy and electron affinity, the problem of improving the insulation performance of natural ester is solved, providing microscopic technical guidance, and improving the prediction and optimization of lightning impact performance ability.
Patent Information
- Application Number
- CN202411306599.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-19
- Publication Date
- 2024-12-31
AI Technical Summary
The prior art lacks effective methods to improve the insulation properties of natural esters from the perspective of chemical structure, especially in lightning impact properties, and there is less analysis of the ionization energy and electron affinity of triglycerides.
By constructing a set of feature quantities of key molecular descriptors that characterize the impact insulation properties of natural esters, calculate their ionization energy and electron affinity, and select closely related molecular descriptors to perform ionization energy and electron affinity of different types of natural ester molecules. Comparative analysis of the psychiatric energy, and the density functional theory and correlation coefficient method are used to filter key descriptors.
The quantitative description of the ionization energy and electron affinity properties of natural ester molecules is achieved, and technical guidance is provided for the development of natural ester products with strong impact insulation performance from the microscopic level, which improves the prediction and optimization capabilities of lightning impact performance.
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Figure CN119230007A_ABST
Abstract
Description
Technical Field
[0001] The invention belongs to the technical field of liquid dielectric insulation performance analysis and relates to an analysis method for determining factors affecting ionization energy and electron affinity of triglyceride molecules. Background Art
[0002] Mineral oil has been used in transformers for more than 100 years. In recent years, mineral oil transformers have frequently caught fire and exploded. Once mineral oil leaks, it will cause great pollution to the environment. Natural esters have the advantages of anti-aging, environmental protection, excellent fire resistance, and renewability, which can meet the development needs of dielectric liquids in the future. At present, there are more than 1 million natural ester insulating oil transformers in operation worldwide, with voltage levels ranging from 10kV to 420kV and capacities ranging from 6.25MVA to 300MVA. In the future, the number of natural ester transformers will continue to increase.
[0003] The breakdown performance of natural esters is the basic electrical performance for judging their use as insulating liquid dielectrics. Many researchers have experimentally explored the breakdown voltage of natural esters under different conditions and compared them with mineral oils. They found that the power frequency breakdown voltage of natural esters is generally greater than that of mineral oils, but their lightning impulse voltage is significantly lower than that of mineral oils. The lightning impulse breakdown voltage of oil products is less affected by impurities such as water, but is closely related to the ability of the chemical results of the oil products themselves to bind electrons. Among the parameters related to the electronic properties of molecules, the ionization energy (IP) indicates the ability of ground-state atoms to lose ground-state electrons and become cations, reflecting the ionization stability of substances; the electron affinity (EA) indicates the difficulty of molecules to capture electrons. Therefore, the ionization energy (IP) and the electron affinity (EA) have an important influence on the lightning impulse performance of liquid insulating media. However, there are currently few analyses of the ionization energy and electron affinity of natural esters, resulting in a lack of an effective method to improve the insulation performance of oil products based on the chemical structure itself. Summary of the invention
[0004] In view of this, an object of the present invention is to provide an analytical method for determining the factors affecting the ionization energy and electron affinity of triglyceride molecules.
[0005] In order to achieve the above object, the present invention provides the following technical solutions:
[0006] In a first aspect, the present invention provides an analytical method for determining the factors affecting the ionization energy and electron affinity of triglyceride molecules, comprising the following steps:
[0007] Construct a set of key molecular descriptor features to characterize the impact insulation performance of natural esters;
[0008] Calculate the ionization energy and electron affinity of natural ester insulating oil molecules;
[0009] Choose molecular descriptors that are closely related to ionization energy and electron affinity;
[0010] Molecular descriptors were used to compare and analyze the ionization energies and electron affinities of different types of natural ester molecules.
[0011] Furthermore, the construction of a key molecular descriptor feature set characterizing the impact insulation performance of natural esters specifically includes: based on Koopman's theorem, frontier orbital theory, the influence of atomic size on the ability of atomic nuclei to bind electrons, and the influence of electrostatic potential on the confrontation between atomic nuclei and electrons in molecules, key molecular descriptors that affect the insulation performance of oil products are selected to construct a key molecular descriptor feature set characterizing the impact insulation performance of natural esters.
[0012] Furthermore, the key molecular descriptor feature set includes: molecular relative molecular mass MW, van der Waals surface Svdw, molecular volume Vvdw, carbon-hydrogen ratio C:H, highest occupied orbital energy level E HOMO , the lowest unoccupied orbital energy level E LUMO , energy gap Egap, positive polarity electrostatic potential surface area S+, negative polarity electrostatic potential surface area S-, electrostatic potential average value Vp, positive polarity electrostatic potential average value V p +, negative polarity electrostatic potential average value V p -, electrostatic potential variance σ, positive electrostatic potential variance σ+, negative electrostatic potential variance σ-, Pi index Pi, molecular polarity index Ind-p, polar surface area (Sp), non-polar surface area (S-np).
[0013] Further, the calculation of the ionization energy and electron affinity of the natural ester insulating oil molecule specifically includes: constructing an insulating oil molecular model based on density functional theory, and using M062X functional with 6-311G (d, p) basis set to calculate the energy of neutral molecules, cations and anions in the constructed insulating oil molecular model, as shown in formulas (1) and (2); the value of the ionization energy of the insulating oil molecule is the energy of the insulating oil cation molecule minus the energy of the insulating oil neutral molecule, and the value of the electron affinity is the energy of the insulating oil neutral molecule minus the energy of the insulating oil anion molecule;
[0014] IP=E M+ -E M (1)
[0015] EA=E M -E M- (2)
[0016] Where E M is the energy calculated when the insulating oil molecule is neutral, E M+ is the energy calculated when the charge of the insulating oil molecule is +1, E M- The energy calculated when the charge of the insulating oil molecule is -1.
[0017] Furthermore, the selection and determination of molecular descriptors closely associated with ionization energy and electron affinity includes: testing all molecular descriptors through normal distribution, using Pearson correlation coefficient method and Spearman correlation coefficient method to describe the correlation between molecular descriptors that conform to normal distribution and those that do not conform to normal distribution and ionization energy and electron affinity, respectively, and then screening key molecular descriptors with the strongest correlation.
[0018] Further, the selecting of molecular descriptors closely related to ionization energy and electron affinity comprises the following steps:
[0019] Step 1: Use the Shapiro-Wilk method suitable for small sample data to perform a normal distribution test on all molecular descriptors, and calculate the statistic W to quantify the difference between the sample data and the normal distribution. The value range of W is between 0 and 1. A value close to 1 indicates that the sample data fits the normal distribution well, otherwise it indicates a poor fit, as shown in equations (3) and (4):
[0020]
[0021] In the formula, x i is the i-th order statistic, that is, the i-th minimum number in the sample, is the sample mean, m is the expected value of ordered independent and identically distributed statistics sampled from a standard normally distributed random variable, and V is the covariance of these ordered statistics;
[0022] For molecular descriptors whose data conform to normal distribution, the Pearson correlation coefficient is used to describe the correlation with the dependent variable, as shown in formula (5). For those that do not conform to normal distribution, the Spearman correlation coefficient method is used, as shown in formula (6):
[0023]
[0024] In the formula, γ is the Pearson correlation coefficient, ρ is the Spearman correlation coefficient, is the mean value of the sample;
[0025] Step 2: According to the correlation coefficients between ionization energy, electron affinity and molecular descriptors, select S(-), EHM, Egap, Vp(-), σ+, C:H as the key molecular descriptors of ionization energy; select E LUMO is the key molecular descriptor for electron affinity.
[0026] Furthermore, the use of molecular descriptors to conduct comparative analysis of ionization energies and electron affinities of different types of natural ester molecules specifically includes: based on the correlation between ionization energies and electron affinities of different molecular descriptors, comparative analysis of differences in molecular descriptor values of different molecules, and further comparative analysis in combination with lightning impulse breakdown characteristics of different oil products.
[0027] In a second aspect, the present invention provides an analytical device for determining the factors affecting the ionization energy and electron affinity of triglyceride molecules, comprising:
[0028] Building module: used to construct a set of key molecular descriptor features to characterize the impact insulation performance of natural esters;
[0029] Calculation module: used to calculate the ionization energy and electron affinity of natural ester insulating oil molecules;
[0030] Determination module: used to select molecular descriptors that are closely related to ionization energy and electron affinity;
[0031] Analysis module: used to compare the ionization energy and electron affinity of different types of natural ester molecules using molecular descriptors.
[0032] In a third aspect, the present invention provides an electronic device, including a memory and a processor;
[0033] The memory is used to store computer programs;
[0034] The processor is used to implement any of the above-mentioned analytical methods for determining factors affecting the ionization energy and electron affinity of triglyceride molecules when executing the computer program.
[0035] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the analytical method for determining factors affecting the ionization energy and electron affinity of triglyceride molecules as described above is implemented.
[0036] The beneficial effects of the present invention are: ionization energy (IP) and electron affinity (EA) have an important influence on the lightning impulse performance of liquid insulating media. At present, there are few microscopic studies on the ionization and affinity of natural esters, and the inherent microscopic properties of molecules are not considered. The present invention proposes an analytical method for determining the ionization energy and electron affinity of triglyceride molecules, including four aspects: constructing a set of key molecular descriptor feature quantities that characterize the impact insulation performance of natural esters; calculating the ionization energy and electron affinity of natural ester insulating oil molecules; preferably determining molecular descriptors that are closely related to ionization energy and electron affinity; using molecular descriptors to carry out comparative analysis of ionization energy and electron affinity of different types of natural ester molecules. The method of the present invention realizes quantitative description of the ionization energy and affinity properties of natural ester molecules, provides new ideas for mastering the ionization energy and electron affinity of different types of natural ester molecules at a microscopic level, and further provides technical guidance for the development of natural ester products with strong impact insulation performance.
[0037] Other advantages, objectives and features of the present invention will be described in the following description to some extent, and to some extent, will be obvious to those skilled in the art based on the following examination and study, or can be taught from the practice of the present invention. The objectives and other advantages of the present invention can be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS
[0038] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be described in detail below in conjunction with the accompanying drawings, wherein:
[0039] Figure 1 Flow chart of the analytical method for determining the factors that affect the ionization energy and electron affinity of triglyceride molecules;
[0040] Figure 2 Figure 2 is a graph showing the correlation coefficients between ionization energy and electron affinity and molecular descriptors. (a) is the correlation coefficient between ionization energy and molecular descriptors, and (b) is the correlation coefficient between electron affinity and molecular descriptors. DETAILED DESCRIPTION
[0041] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner, and the following embodiments and features in the embodiments can be combined with each other without conflict.
[0042] It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present invention, and thus the drawings only show components related to the present invention rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.
[0043] In the following description, numerous details are discussed to provide a more thorough explanation of the embodiments of the present invention. However, it is obvious to those skilled in the art that the embodiments of the present invention can be implemented without these specific details. In other embodiments, well-known structures and devices are shown in the form of block diagrams rather than in detail to avoid making the embodiments of the present invention difficult to understand.
[0044] The present invention provides an analytical method for determining the factors affecting the ionization energy and electron affinity of triglyceride molecules. In this embodiment, the method is implemented by the following steps:
[0045] Step 1: Construct a set of key molecular descriptor features that characterize the impact insulation performance of natural esters. Based on Koopmans' theorem, frontier orbital theory, the effect of atomic size on the ability of nuclei to bind electrons, and the effect of electrostatic potential on the confrontation between nuclei and electrons in molecules, 19 key molecular descriptors that affect the insulation performance of oil products are selected to construct a set of key molecular descriptor features that characterize the impact insulation performance of natural esters. Koopmans' theorem states that in the closed-shell Hartree-Fock theory (HF), the first ionization energy of a molecular system is equal to the negative of the energy of the highest occupied molecular orbital (HOMO); according to the frontier orbital theory, the highest occupied molecular orbital mainly acts as an electron donor, and the lowest unoccupied molecular orbital mainly acts as an electron acceptor. The energy of the frontier orbital is related to the electronic stability of the molecule; the electrostatic potential describes the result of the confrontation between nuclei and electrons in the molecule; the variance of the electrostatic potential quantifies the degree of fluctuation of the electrostatic potential at each point relative to the average electrostatic potential. These descriptors characterize the fluctuation amplitude of positive and negative electrostatic potential on the molecular surface; 19 key molecular descriptors that affect the insulation performance of oil products are selected, as shown in Table 1, namely molecular relative molecular mass MW, van der Waals surface Svdw, molecular volume Vvdw, carbon-hydrogen ratio C:H, highest occupied orbital energy level E HOMO , the lowest unoccupied orbital energy level E LUMO , energy gap Egap, positive polarity electrostatic potential surface area S+, negative polarity electrostatic potential surface area S-, electrostatic potential average value Vp, positive polarity electrostatic potential average value V p +, negative polarity electrostatic potential average value V p -, electrostatic potential variance σ, positive electrostatic potential variance σ+, negative electrostatic potential variance σ-, Pi index Pi, molecular polarity index Ind-p, polar surface area (Sp), non-polar surface area (S-np). In this way, a set of key molecular descriptor feature quantities that characterize the impact insulation properties of natural esters is constructed.
[0046] Table 1
[0047] category Molecular descriptors size MW, Svdw, Vvdw, C:H energy level <![CDATA[E HOMO ,AND LUMO ,AND gap ]]> Electrostatic potential S(-), S(+), Vp, Vp+, Vp-, σ, σ+, σ-, Pi polarity Ind-p, Sp, S-np
[0048] Step 2: Calculate the ionization energy and electron affinity of natural ester insulating oil molecules. Based on density functional theory, a molecular model of insulating oil was constructed, and the values of ionization energy and electron affinity of the insulating oil molecular model were calculated using Gaussian software using the M062X\\6-311+G(d,p) method. Thirty common triglyceride molecules detectable in soybean oil or rapeseed oil were selected: AOL, AoLO, AoOO, OLS, PLnS, PLO, PLP, POO, POP, POS, BLL, SSS, OOO, LLL, LnLnLn, PPP, LLnLn, LLO, LLP, LnLL, LiOL, PLnP, AoLnE, AOO, PLLn, BLO, BOO, ELE, ELnP, LnLO (where S represents stearic acid, P represents palmitic acid, A represents arachidic acid, Ao represents arachidic acid, O represents oleic acid, L represents linoleic acid, Ln represents linolenic acid, E represents erucic acid, Li represents lignoceric acid, and B represents behenic acid), and 30 triglyceride molecular system models were constructed based on molecular dynamics theory.
[0049] Based on density functional theory, Gaussian software was used to calculate the energy of neutral molecules, cations and anions for the constructed insulating oil molecular model using the M062X functional combined with the 6-311G (d, p) basis set, as shown in equations (1) and (2). The ionization energy of the insulating oil molecule is the energy of the insulating oil cation molecule minus the energy of the insulating oil neutral molecule, and the electron affinity is the energy of the insulating oil neutral molecule minus the energy of the insulating oil anion molecule.
[0050] IP=E M+ -E M (1)
[0051] EA=E M -E M- (2)
[0052] Where E M is the energy calculated when the insulating oil molecule is neutral, E M+ is the energy calculated when the charge of the insulating oil molecule is +1, E M- The energy calculated when the charge of the insulating oil molecule is -1.
[0053] Table 2 shows the calculation results of ionization energy and electron affinity of triglyceride molecules.
[0054] Table 2
[0055]
[0056]
[0057] Step 3: Preferentially determine the molecular descriptors that are closely related to ionization energy and electron affinity. All molecular descriptors are tested by normal distribution. The Pearson correlation coefficient method and the Spearman correlation coefficient method are used to describe the correlation between the molecular descriptors that conform to the normal distribution and those that do not conform to the normal distribution, respectively, and then the key molecular descriptors with the strongest correlation are screened. The Shapiro-Wilk method suitable for small sample data is used to test the normal distribution of all molecular descriptors. This method quantifies the difference between the sample data and the normal distribution by calculating the statistic W. The value range of W is between 0 and 1. A value close to 1 indicates that the sample data fits the normal distribution well, otherwise, it indicates a poor fit, as shown in formulas (3) and (4). For molecular descriptors whose data conform to the normal distribution, the Pearson correlation coefficient is used to describe the correlation with the dependent variable, as shown in formula (5). For those that do not conform to the normal distribution, the Spearman correlation coefficient method is used, as shown in formula (6).
[0058]
[0059] In the formula, x i is the i-th order statistic, that is, the i-th minimum number in the sample, is the sample mean, m is the expected value of ordered independent and identically distributed statistics sampled from a standard normally distributed random variable, and V is the covariance of these ordered statistics.
[0060]
[0061]
[0062] In the formula, γ is the Pearson correlation coefficient, ρ is the Spearman correlation coefficient, is the sample mean.
[0063] like Figure 2 (a)-(b) and Table 3 are correlation coefficient charts of ionization energy, electron affinity and molecular descriptors.
[0064] Table 3
[0065]
[0066] S(-),E HOMO , Egap, Vp(-), σ+, C:H and ionization energy are obviously correlated, which can be used to describe the ionization energy of natural ester molecules. Among them, Egap and Vp(-) are positively correlated with ionization energy, S(-), E HOMO , σ+, and C:H are negatively correlated with the ionization energy, so S(-), EHM, Egap, Vp(-), σ+, and C:H were selected as the key molecular descriptors of ionization energy. LUMOIt has a clear negative correlation with electron affinity, so E was selected. LUMO is the key molecular descriptor for electron affinity.
[0067] Step 4: Use molecular descriptors to conduct comparative analysis of ionization energy and electron affinity of different types of natural ester molecules. Based on the correlation between ionization energy and electron affinity of different molecular descriptors, the differences in molecular descriptor values of different molecules are compared and analyzed, and further comparative analysis is conducted in combination with the lightning impulse breakdown characteristics of different oil products, providing new ideas for mastering the ionization energy and electron affinity of different types of natural ester molecules, and thus providing technical guidance for the development of natural ester products with strong impact insulation performance.
[0068] Embodiment 1:
[0069] List the S(-), E(-) and E(-) of trioleylglycerol (OOO) and trilinoleylglycerol (LLL) molecules. HOMO ,Egap,Vp(-),σ+,C:H,E LUMO Seven key molecular descriptor values and their corresponding ionization energies and electron affinities; OOO and LLL lightning impulse breakdown characteristic tests were carried out at the same time. The test adopted a step-by-step voltage step-up method to carry out the lightning impulse breakdown test of the insulating oil. The electrodes were needle-plate electrodes with an electrode spacing of 25 mm, as shown in Table 4.
[0070] Table 4
[0071]
[0072] OOO and LLL molecular descriptors E HOMO , Egap, Vp(-), σ+, C: The difference of H value is small, which has little effect on ionization energy, while the difference of S(-) is large. The correlation coefficient between S(-) and ionization energy is -0.483, showing a negative correlation. Moreover, the S(-) value of OOO is smaller than that of LLL. Therefore, the ionization energy value of OOO should be higher than that of LLL. LUMO It is a key molecular descriptor for characterizing electron affinity and is negatively correlated with affinity. LUMO The value is less than LLL, so the electron affinity value of OOO should be higher than LLL. The data in the table show that the trend of the change of ionization energy and electron affinity represented by the molecular descriptor is consistent with the theoretical calculation; the discharge characteristics of natural ester molecules will be affected by ionization energy and electron affinity. Generally speaking, the greater the ionization energy, the better the lightning impulse breakdown characteristics of natural ester molecules. The ionization energy value of OOO is higher than LLL, so theoretically the lightning impulse breakdown voltage value of OOO should be higher than LLL; after conducting lightning impulse breakdown characteristics tests of OOO and LLL, it was found that the lightning impulse breakdown voltage of OOO is indeed higher than LLL in both positive and negative polarities, which is consistent with the theory.
[0073] In the above embodiments, the description's reference to "this embodiment" indicates that a particular feature, structure, or characteristic described in conjunction with the embodiment is included in at least some embodiments, but not necessarily all embodiments. Multiple occurrences of "this embodiment" do not necessarily all refer to the same embodiment.
[0074] In the above-described embodiments, although the invention has been described in conjunction with specific embodiments of the invention, many substitutions, modifications, and variations of these embodiments will be apparent to those of ordinary skill in the art based on the foregoing description. For example, other storage structures (e.g., dynamic RAM (DRAM)) may use the embodiments discussed. Embodiments of the invention are intended to encompass all such substitutions, modifications, and variations that fall within the broad scope of the appended claims.
[0075] This embodiment further provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, any one of the methods in this embodiment is implemented.
[0076] This embodiment also provides an electronic terminal, including: a processor and a memory;
[0077] The memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the terminal executes any one of the methods in this embodiment.
[0078] The computer-readable storage medium in this embodiment can be understood by ordinary technicians in this field: all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to the computer program. The aforementioned computer program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk and other media that can store program codes.
[0079] The electronic terminal provided in this embodiment includes a processor, a memory, a transceiver and a communication interface. The memory and the communication interface are connected to the processor and the transceiver and complete communication with each other. The memory is used to store computer programs, the communication interface is used to communicate, and the processor and the transceiver are used to run computer programs so that the electronic terminal executes each step of the above method.
[0080] In this embodiment, the memory may include a random access memory (RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.
[0081] The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.
[0082] The present invention can be used in many general or special computing system environments or configurations, such as personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and the like.
[0083] The present invention may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.
[0084] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution, which should be included in the scope of the claims of the present invention.
Claims
1. An analytical method for determining the factors affecting the ionization energy and electron affinity of triglyceride molecules, characterized in that: The following steps are involved: Construct a set of key molecular descriptor features to characterize the impact insulation performance of natural esters; Calculate the ionization energy and electron affinity of natural ester insulating oil molecules; Choose molecular descriptors that are closely related to ionization energy and electron affinity; Molecular descriptors were used to compare and analyze the ionization energies and electron affinities of different types of natural ester molecules.
2. The analytical method for determining the factors affecting the ionization energy and electron affinity of triglyceride molecules according to claim 1, characterized in that: The method of constructing a key molecular descriptor feature quantity set for characterizing the impact insulation performance of natural esters specifically includes: based on the Koopman theorem, frontier orbital theory, the influence of atomic size on the ability of atomic nuclei to bind electrons, and the influence of electrostatic potential on the confrontation between atomic nuclei and electrons in molecules, selecting key molecular descriptors that affect the insulation performance of oil products, and constructing a key molecular descriptor feature quantity set for characterizing the impact insulation performance of natural esters.
3. The analytical method for determining the factors affecting the ionization energy and electron affinity of triglyceride molecules according to claim 2, characterized in that: The key molecular descriptor feature set includes: molecular relative molecular mass MW, van der Waals surface Svdw, molecular volume Vvdw, carbon-hydrogen ratio C:H, highest occupied orbital energy level E HOMO , the lowest unoccupied orbital energy level E LUMO , energy gap Egap, positive polarity electrostatic potential surface area S+, negative polarity electrostatic potential surface area S-, electrostatic potential average value Vp, positive polarity electrostatic potential average value V p +, negative polarity electrostatic potential average value V p -, electrostatic potential variance σ, positive electrostatic potential variance σ+, negative electrostatic potential variance σ-, Pi index Pi, molecular polarity index Ind-p, polar surface area (Sp), non-polar surface area (S-np).
4. The analytical method for determining the factors affecting the ionization energy and electron affinity of triglyceride molecules according to claim 1, characterized in that: The method for calculating the ionization energy and electron affinity of the natural ester insulating oil molecule specifically comprises: constructing an insulating oil molecule model based on density functional theory, and using M062X functional with 6-311G (d, p) basis set to calculate the energy of neutral molecules, cations and anions in the constructed insulating oil molecule model, as shown in formulas (1) and (2); the value of the ionization energy of the insulating oil molecule is the energy of the insulating oil cation molecule minus the energy of the insulating oil neutral molecule, and the value of the electron affinity is the energy of the insulating oil neutral molecule minus the energy of the insulating oil anion molecule; IP=E M+ -E M (1) YES=Yes M -Yes M- (2) Where E M is the energy calculated when the insulating oil molecule is neutral, E M+ is the energy calculated when the charge of the insulating oil molecule is +1, E M- The energy calculated when the charge of the insulating oil molecule is -1.
5. The analytical method for determining the factors affecting the ionization energy and electron affinity of triglyceride molecules according to claim 1, characterized in that: The method of selecting molecular descriptors closely related to ionization energy and electron affinity includes: testing all molecular descriptors through normal distribution, using Pearson correlation coefficient method and Spearman correlation coefficient method to describe the correlation between molecular descriptors that conform to normal distribution and molecular descriptors that do not conform to normal distribution and ionization energy and electron affinity, respectively, and then screening key molecular descriptors with the strongest correlation.
6. The analytical method for determining the factors affecting the ionization energy and electron affinity of triglyceride molecules according to claim 5, characterized in that: The step of selecting a molecular descriptor that is closely related to ionization energy and electron affinity comprises the following steps: Step 1: Use the Shapiro-Wilk method suitable for small sample data to perform a normal distribution test on all molecular descriptors, and calculate the statistic W to quantify the difference between the sample data and the normal distribution. The value range of W is between 0 and 1. A value close to 1 indicates that the sample data fits the normal distribution well, otherwise it indicates a poor fit, as shown in equations (3) and (4): In the formula, x i is the i-th order statistic, that is, the i-th minimum number in the sample, is the sample mean, m is the expected value of ordered independent and identically distributed statistics sampled from a standard normally distributed random variable, and V is the covariance of these ordered statistics; For molecular descriptors whose data conform to normal distribution, the Pearson correlation coefficient is used to describe the correlation with the dependent variable, as shown in formula (5). For those that do not conform to normal distribution, the Spearman correlation coefficient method is used, as shown in formula (6): In the formula, γ is the Pearson correlation coefficient, ρ is the Spearman correlation coefficient, is the mean value of the sample; Step 2: According to the correlation coefficients between ionization energy, electron affinity and molecular descriptors, select S(-), EHM, Egap, Vp(-), σ+, C:H as the key molecular descriptors of ionization energy; select E LUMO is the key molecular descriptor for electron affinity.
7. The analytical method for determining the factors affecting the ionization energy and electron affinity of triglyceride molecules according to claim 1, characterized in that: The comparative analysis of ionization energy and electron affinity of different types of natural ester molecules using molecular descriptors specifically includes: based on the correlation between ionization energy and electron affinity of different molecular descriptors, comparative analysis of differences in molecular descriptor values of different molecules, and further comparative analysis in combination with lightning impulse breakdown characteristics of different oil products.
8. An analytical device for determining factors affecting the ionization energy and electron affinity of triglyceride molecules, characterized in that: include: Building module: used to construct a set of key molecular descriptor features to characterize the impact insulation performance of natural esters; Calculation module: used to calculate the ionization energy and electron affinity of natural ester insulating oil molecules; Determination module: used to select molecular descriptors that are closely related to ionization energy and electron affinity; Analysis module: used to compare the ionization energy and electron affinity of different types of natural ester molecules using molecular descriptors.
9. An electronic device, characterized in that: including memory and processor; The memory is used to store computer programs; The processor is used to implement the analytical method for determining the factors affecting the ionization energy and electron affinity of triglyceride molecules as described in any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by the processor, the analytical method for determining factors affecting the ionization energy and electron affinity of triglyceride molecules as described in any one of claims 1 to 7 is implemented.