Method for calculating products of gas discharge taking into account electron collision energy and related device
Patent Information
- Application Number
- CN202311789379.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2023-12-22
- Publication Date
- 2026-10-13
- Estimated Expiration
- 2043-12-22
AI Technical Summary
绝缘气体分解后其绝缘性能和灭弧能力可能会大幅降低，影响电力设备的性能及寿命
[0045]本申请的目的在于通过AIMD法计算不同入射电子能量下发生碰撞电离后气体的离子产物、电离解离通道及计算质谱，从而提供了不同放电工况、放电能量下环保新气体分解特性的计算方法。本申请无需对电离后解离路径进行假设并计算相关反应速率，而直接通过从头算动力学模拟计算大量轨迹，从而确定具有统计意义的质谱图。因此该方法在计算大分子时能表现出明显的优势，避免繁琐计算。本申请可以在给定分子结构的情况下，对气体分子未知分解产物的具体分子结构进行计算验证，还可以以此分析其在放电情况下可能形成的离子，进一步了解气体放电过程中的离子过程。
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Figure CN117744459B_ABST
Abstract
Description
Technical Field
[0001] This application belongs to the field of electrical insulation medium technology, and relates to a method and related apparatus for calculating gas discharge products that takes into account electron collision energy, based on ab initio molecular dynamics (AIMD). Background Technology
[0002] The decomposition characteristics of insulating gases are crucial for the stable operation of electrical equipment. Environmentally friendly insulating gases have numerous and complex molecular structures. Under discharge conditions, gas molecules may decompose not only due to localized high temperatures, but their decomposition characteristics are also significantly affected by electron collisions. Whether in spark discharge or partial discharge conditions, a large number of free electrons are accelerated under the influence of the electric field and collide with gas molecules. This interaction between electrons and gas molecules can lead to ionization of the gas, generating new free electrons. Both the incident electrons and the newly ionized electrons may carry unknown energy upon exiting the gas. In this situation, gas molecules gain additional energy from the incident electrons, becoming excited to higher electronic states, or their chemical bonds break, forming various ionic products. After the insulating gas decomposes, its insulating properties and arc-quenching ability may be significantly reduced, affecting the performance and lifespan of electrical equipment.
[0003] Theoretical calculations of the decomposition characteristics of environmentally friendly gases currently often employ Distributed Fourier Transform (DFT) to calculate energy changes and reaction rates along different decomposition pathways. While this method effectively reflects the influence of temperature changes, it fails to capture the aforementioned variations in incident electron energy. Therefore, it is necessary to propose a calculation method for gas decomposition characteristics that considers collisions with incident electrons of different energies, enabling the study of the decomposition mechanism of environmentally friendly gases under different discharge conditions and energies. Summary of the Invention
[0004] The purpose of this application is to solve the problems in the prior art and provide a method and related device for calculating gas discharge products that consider electron collision energy. This application can determine the ion products and ionization channels after collision ionization under different incident electron energies, obtain the calculated mass spectrometry through statistical analysis, and thus calculate the decomposition mechanism and decomposition characteristics of environmentally friendly new gases under different discharge conditions and discharge energies.
[0005] To achieve the above objectives, this application adopts the following technical solution:
[0006] In a first aspect, this application provides a method for calculating gas discharge products that takes into account electron collision energy, comprising the following steps:
[0007] The target molecule was subjected to a thermal bath under a canonical ensemble. After reaching pre-equilibrium, it was simulated under a microcanonical ensemble. The MD trajectory was randomly sampled several times during the simulation period to obtain several system structures and atomic nuclei velocities.
[0008] Mulliken population analysis was performed on several system architectures and nuclear velocities to obtain the nuclear velocity scaling factor.
[0009] Starting with a randomly sampled architecture, the velocities of each atomic nucleus are modified by a nuclear velocity amplification scaling factor. Each architecture is simulated under a microcanonical ensemble to obtain several dissociation paths and physical images of ionic products.
[0010] By statistically analyzing several dissociation paths and ionic product physical images of several MD trajectories, the mass spectrometry calculation results of the target molecule are obtained.
[0011] Furthermore, this application subjects the target molecule to a thermal bath under a canonical ensemble, and after reaching pre-equilibrium, it is simulated under a microcanonical ensemble, specifically as follows:
[0012] After reaching pre-equilibrium, the system was simulated for 12.5 ps in a 500 K hot bath and then for 25 ps under a microcanonical ensemble.
[0013] Furthermore, the target molecule in this application is a gas molecule, a positive ion, or a negative ion.
[0014] Furthermore, this application performs Mulliken population analysis on several system architectures and nuclear velocities to obtain nuclear velocity scaling factors, including:
[0015] A single-point energy calculation was performed on several system structures at the PBE0 / def2-SV(P) level to obtain the molecular orbital spectrum at this time. Based on the molecular orbital spectrum and atomic nuclear velocity of the sampled structure, the extra internal energy, internal energy conversion time and nuclear velocity amplification factor of the system were calculated using Mulliken population analysis.
[0016] Furthermore, the minimum value of the additional internal energy (IEE) in this application system is 0, i.e., IEE min =0; the maximum is the incident electron energy E impact With HOMO level ε HOMO The difference, i.e., IEE max =E impact -ε HOMO For each sampling structure, the value of IEE is generated randomly and follows a Poisson distribution as follows:
[0017]
[0018] Where P(E) is the probability that the system’s extra internal energy IEE equals E; E is the energy value obtained by the system after the collision; a, b, and c are calculation parameters, the values of which change with the system, and the goal is to make P(E) take the maximum value when IEE is (0.6eV * number of atoms);
[0019] The internal energy conversion time t IC as follows:
[0020]
[0021] Where M is the order number of HOMO; α and k h The constant is 0.5 eV. -1 and 2ps; N el ε is the number of valence electrons in the system; i and ε j These are the energies of the i-th molecular orbital and the j-th molecular orbital, respectively.
[0022] The nuclear velocity amplification factor f v as follows:
[0023]
[0024] Where m is the atomic mass and v0 is the nuclear velocity.
[0025] Furthermore, starting with a randomly sampled architecture, this application modifies the velocities of each atomic nucleus by adjusting the nuclear velocity scaling factor, and simulates each architecture under a microcanonical ensemble to obtain several dissociation paths and physical images of ionic products, including:
[0026] The scaling factor f is amplified by the nuclear velocity. v Modify the velocity v of each atomic nucleus:
[0027] v = f v v0
[0028] Next, each architecture is simulated under a microcanonical ensemble for a preset time, causing all architectures M to undergo valence layer ionization to form M0. + And during the simulated time period, M + All ions are capable of relaxation.
[0029] Furthermore, in this application, when simulating each architecture under a microcanonical ensemble, if M... + For ion dissociation, it is necessary to identify the positively charged particles that contribute to the mass spectrum among the two or more fragment particles produced. The specific method is as follows:
[0030] Calculate the vertical ionization potential VIP of each fragment particle i produced by dissociation. i :
[0031] VIP i =E scf，i (Q-1)-E scf，i (Q)
[0032] Where Q is the number of electrons when the particle is electrically neutral, and E scf，i (Q) and E scf，i (Q-1) represents the electron energy in the two states before and after ionization;
[0033] Calculate the statistical charge of each segment:
[0034]
[0035]
[0036] Among them, C i k is the statistical weight of segment i. B T is the Boltzmann constant. av E is the average temperature of the system. kin The system's kinetic energy is represented by N, the number of atoms is N, and the weights are C. i Larger fragments are positively charged particles that contribute to the mass spectrum.
[0037] Secondly, this application provides a gas discharge product calculation system that considers electron collision energy, comprising:
[0038] The random sampling module is used to heat the target molecule under a canonical ensemble, and after reaching pre-equilibrium, simulate it under a microcanonical ensemble. It also performs several random samplings on the MD trajectory during the simulation period to obtain several system structures and atomic nuclei velocities.
[0039] The population analysis module is used to perform Mulliken population analysis on several system architectures and nuclear velocities to obtain the nuclear velocity amplification factor.
[0040] The path product calculation module is used to simulate each architecture under a microcanonical ensemble by modifying the velocity of each atomic nucleus through a nuclear velocity amplification scaling factor, starting from a randomly sampled architecture, and obtaining several dissociation paths and physical images of ionic products.
[0041] The data statistics module is used to perform statistical analysis on several dissociation paths and ionic product physical images of several MD trajectories to obtain the mass spectrometry calculation results of the target molecule.
[0042] Thirdly, this application provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method described above.
[0043] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method described above.
[0044] Compared with the prior art, this application has the following beneficial effects:
[0045] The purpose of this application is to calculate the ionic products, ionization dissociation channels, and calculated mass spectra of gases after collisional ionization under different incident electron energies using the AIMD method, thereby providing a calculation method for the decomposition characteristics of environmentally friendly new gases under different discharge conditions and energies. This application eliminates the need to assume dissociation pathways after ionization and calculate related reaction rates; instead, it directly calculates a large number of trajectories through ab initio kinetic simulations to determine statistically significant mass spectra. Therefore, this method exhibits significant advantages when calculating macromolecules, avoiding tedious calculations. Given a molecular structure, this application can calculate and verify the specific molecular structure of unknown decomposition products of gas molecules, and can also analyze the ions that may be formed under discharge conditions, further understanding the ionic processes during gas discharge. Attached Figure Description
[0046] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.
[0047] Figure 1 This is a flowchart of the method described in this application.
[0048] Figure 2 This is a schematic diagram of the system in this application.
[0049] Figure 3 A flowchart of a method for calculating the environmental gas decomposition characteristics of incident electron collisions with different energies for this application;
[0050] Figure 4 This is an ionization and dissociation path of C4F7N calculated in this application during a kinetic simulation process;
[0051] Figure 5 To apply the C5F calculated in this application 10 One ionization and dissociation path of O in the dynamic simulation process;
[0052] Figure 6 To apply the environmentally friendly gases C4F7N and C5F calculated in this application 10 Theoretical calculated mass spectrometry of O and its comparison with experimental mass spectrometry;
[0053] Figure 7 To apply the different incident electron energies calculated in this application for C4F7N and C5F 10 Theoretical calculation of O mass spectrometry. Detailed Implementation
[0054] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.
[0055] Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.
[0056] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.
[0057] In the description of the embodiments of this application, it should be noted that if terms such as "upper," "lower," "horizontal," or "inner" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product of the invention is in use, they are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on this application. In addition, terms such as "first" and "second" are only used to distinguish descriptions and should not be construed as indicating or implying relative importance.
[0058] Furthermore, the use of the term "horizontal" does not imply that the component must be absolutely horizontal, but rather that it can be slightly tilted. For example, "horizontal" simply means that its direction is more horizontal than "vertical," and does not mean that the structure must be completely horizontal, but can be slightly tilted.
[0059] In the description of the embodiments of this application, it should also be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," "connect," and "link" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.
[0060] Definitions:
[0061] AIMD: Ab initio molecular dynamics. It is a computational method that uses quantum mechanics principles and computer simulations to study the properties and behavior of molecules and materials.
[0062] Ab initio molecular dynamics methods start with the Hamiltonian of a molecular system and use numerical solutions to the Schrödinger equation or density functional theory equations to calculate the structure and properties of molecules. It can simulate the behavior and reactions of molecules under different environments, such as varying temperatures, pressures, and electric fields, as well as changes in molecular configuration, energy, and vibrational frequencies during chemical reactions.
[0063] Ab initio molecular dynamics is widely used in research fields such as materials science, chemistry, and biology. It can simulate the electronic structure, band structure, and optical properties of materials, as well as the mechanisms and dynamics of chemical reactions and the structure and function of biomolecules. Because ab initio molecular dynamics requires significant computational resources, high-performance computers are necessary for its calculations.
[0064] NVT: Constant Volume at Constant Temperature (NVT). In an NVT ensemble, the macroscopic properties of the system do not change over time, but are only related to the system's temperature and volume. This assumption is based on the second law of thermodynamics, which states that when a system is in equilibrium, its entropy (i.e., disorder or disorder) is maximized. In an NVT ensemble, the system's temperature and volume are constant, therefore the system's entropy is also constant.
[0065] The NVT ensemble is a common type of ensemble, suitable for describing systems in equilibrium under isothermal and isochoric conditions. In practical applications, the NVT ensemble can be used to simulate the behavior of matter at specific temperatures and pressures, such as in experimental and computational research in materials science, chemistry, and biology. In the NVT ensemble, the thermodynamic properties of the system can be calculated by integrating the distribution function, such as the system's average energy and entropy.
[0066] NVE: Microcanonical ensemble, also known as "isobaric adiabatic ensemble." In an NVE ensemble, the macroscopic properties of the system do not change over time, but are only related to the system's energy. This assumption is based on the second law of thermodynamics, which states that when a system is in equilibrium, its entropy (i.e., disorder or disorder) is maximized. In an NVE ensemble, the system's pressure and volume are constant, therefore the system's entropy is also constant.
[0067] The NVE ensemble is a common type of ensemble, suitable for describing systems in equilibrium under isobaric and adiabatic conditions. In practical applications, the NVE ensemble can be used to simulate the behavior of matter under specific pressures and temperatures, such as in experimental and computational research in materials science, chemistry, and biology. In the NVE ensemble, the thermodynamic properties of the system can be calculated by integrating the distribution function, such as the system's average energy and entropy.
[0068] MD trajectories: MD trajectories are a data output from molecular dynamics simulations, essentially a set of ordered atomic configurations. Trajectory analysis algorithms can extract meaningful information from this high-dimensional data, such as extracting information about each configuration and calculating the conversion rates between different configurations. This extraction and calculation helps us better understand the behavior and properties of molecules. By analyzing trajectories, we can obtain much information relevant to our current research questions, such as the structure and properties of molecules, the rates and mechanisms of chemical reactions, and so on. Therefore, MD trajectories are one of the important tools for studying molecular structure and properties.
[0069] Mulliken population analysis is an electronic structure calculation method used to study the distribution of electrons and charge transfer between atoms in a molecule. The specific steps are as follows:
[0070] 1. Select two adjacent atoms in the molecular structure and determine the type of bond between them (e.g., covalent bond, ionic bond, etc.).
[0071] 2. Based on the results given by the molecular orbital calculation software, the distribution of electrons in the two atomic orbitals can be obtained, i.e., the Mulliken population.
[0072] 3. By comparing the Mulliken populations of two atoms, we can understand the distribution of electrons between the two atoms and determine the type of bond between them.
[0073] 4. If the Mulliken population between two atoms exhibits an uneven distribution, it means that there is a charge transfer between the two atoms, that is, one atom carries a positive charge and the other atom carries a negative charge.
[0074] The present application will now be described in further detail with reference to the accompanying drawings:
[0075] See Figure 1 This application discloses a method for calculating gas discharge products considering electron collision energy, comprising the following steps:
[0076] S1 heats the target molecule in a canonical ensemble until it reaches pre-equilibrium, then simulates it in a microcanonical ensemble. The MD trajectory is randomly sampled several times during the simulation period to obtain several system structures and atomic nuclei velocities.
[0077] S2 performs Mulliken population analysis on several system architectures and nuclear velocities to obtain the nuclear velocity scaling factor.
[0078] Starting with a randomly sampled architecture, S3 modifies the velocities of each atomic nucleus by adjusting the nuclear velocity amplification scaling factor, and simulates each architecture under a microcanonical ensemble to obtain several dissociation paths and physical images of ionic products.
[0079] S4 performs statistical analysis on several dissociation paths and ionic product physical images of several MD trajectories to obtain the mass spectrometry calculation results of the target molecule.
[0080] In one feasible embodiment of this application, S1 specifically involves 12.5 ps in a 500K hot bath to reach pre-equilibrium, followed by 25 ps simulation under a microcanonical ensemble. In practical applications, the target molecules in this application are gas molecules, positive ions, or negative ions.
[0081] It should be noted that when performing several random samplings of the MD trajectory within the simulation time period, the number of random samplings is generally 25 times or more of the number of atoms, and the number of samplings can be set as needed.
[0082] In another feasible embodiment of this application, a single-point energy calculation is performed on several system architectures at the PBE0 / def2-SV(P) level to obtain the molecular orbital spectrum at this time. Based on the molecular orbital spectrum and atomic nuclear velocity of the sampled structure, the additional internal energy, internal energy conversion time and nuclear velocity amplification factor of the system are calculated using Mulliken population analysis.
[0083] It should be noted that the minimum value of the system's additional internal energy IEE is 0, i.e., IEE min =0; the maximum is the incident electron energy E impact With HOMO (Highest Occupied Molecular Orbital) energy level ε HOMO The difference, i.e., IEE max =E impact -ε HOMO For each sampling structure, the value of IEE is generated randomly and follows a Poisson distribution as follows:
[0084]
[0085] Where P(E) is the probability that the system’s extra internal energy IEE is equal to E; E is the energy value that the system may obtain after the collision; a, b, and c are calculation parameters, the values of which change with the system, and the goal is to make P(E) take the maximum value when IEE is (0.6eV * number of atoms);
[0086] The internal energy conversion time t IC as follows:
[0087]
[0088] Where M is the order number of HOMO; α and k h The constant is 0.5 eV. -1 and 2ps; N el ε is the number of valence electrons in the system; i and ε j These are the energies of the i-th molecular orbital and the j-th molecular orbital, respectively.
[0089] The nuclear velocity amplification factor f v as follows:
[0090]
[0091] Where m is the atomic mass and v0 is the nuclear velocity.
[0092] In another feasible embodiment of this application, the nuclear velocity amplification scaling factor f is used. v Modify the velocity v of each atomic nucleus:
[0093] v = f v v0
[0094] Next, each architecture is simulated under a microcanonical ensemble for a preset time, causing all architectures M to undergo valence layer ionization to form M0. + And during the simulated time period, M +All ions are capable of relaxation.
[0095] In practical applications, when simulating each architecture under a microcanonical ensemble, if M + For ion dissociation, it is necessary to identify the positively charged particles that contribute to the mass spectrum among the two or more fragment particles produced. The specific method is as follows:
[0096] Calculate the vertical ionization potential VIP of each fragment particle i produced by dissociation. i :
[0097] VIP i =E scf，i (Q-1)-E scf，i (Q)
[0098] Where Q is the number of electrons when the particle is electrically neutral, and E scf，i (Q) and E scf，i (Q-1) represents the electron energy in the two states before and after ionization;
[0099] Calculate the statistical charge of each segment:
[0100]
[0101]
[0102] Among them, C i k is the statistical weight of segment i. B T is the Boltzmann constant. av E is the average temperature of the system. kin The system's kinetic energy is represented by N, the number of atoms is N, and the weights are C. i Larger fragments are positively charged particles that contribute to the mass spectrum.
[0103] like Figure 2 As shown in the figure, this application discloses a gas discharge product calculation system that considers electron collision energy, including:
[0104] The random sampling module is used to heat the target molecule under a canonical ensemble, and after reaching pre-equilibrium, simulate it under a microcanonical ensemble. It also performs several random samplings on the MD trajectory during the simulation period to obtain several system structures and atomic nuclei velocities.
[0105] The population analysis module is used to perform Mulliken population analysis on several system architectures and nuclear velocities to obtain the nuclear velocity amplification factor.
[0106] The path product calculation module is used to simulate each architecture under a microcanonical ensemble by modifying the velocity of each atomic nucleus through a nuclear velocity amplification scaling factor, starting from a randomly sampled architecture, and obtaining several dissociation paths and physical images of ionic products.
[0107] The data statistics module is used to perform statistical analysis on several dissociation paths and ionic product physical images of several MD trajectories to obtain the mass spectrometry calculation results of the target molecule.
[0108] The principle of this application:
[0109] This application proposes a calculation method for the decomposition characteristics of environmentally friendly gases considering electron collisions at different incident energies. This method enables the calculation of ionic products and dissociation pathways after collisional ionization of environmentally friendly gases, and provides a deeper understanding of ionic processes during gas discharge. This method eliminates the need to assume dissociation pathways and calculate related reaction rates. Given a molecular structure, it can directly simulate and calculate a large number of trajectories using the AIMD method to verify the specific molecular structures of unknown decomposition products of gas molecules, thereby determining statistically significant mass spectra and obtaining the decomposition mechanism and characteristics of novel environmentally friendly gases under different discharge conditions and energies.
[0110] Example
[0111] like Figure 3 As shown in the figure, this application provides a method for calculating the decomposition characteristics of environmentally friendly gases considering the collisions of incident electrons with different energies based on the AIMD method. The specific method is as follows:
[0112] Step 1: For the target molecule to be calculated by mass spectrometry, the target molecule is first pre-equilibrated for 12.5 ps in a 500 K hot bath under a canonical ensemble (NVT) based on the AIMD method. This is to give each atom in the static initial molecular structure a reasonable velocity. At this temperature, the target molecule will not undergo rapid and significant decomposition, but can easily overcome the conformational transition barrier and thus fully relax. Next, a simulation is performed under a microcanonical ensemble (NVE) for 25 ps, and the MD trajectory is randomly sampled 1000 times during this period to record the system structure and atomic nuclear velocity v0.
[0113] Step 2: For 1000 system architectures, perform a single-point energy calculation at the PBE0 / def2-SV(P) level to obtain the molecular orbital spectrum, and then perform Mulliken population analysis based on this spectrum. Further calculations are then performed to obtain the system's extra internal energy IEE and internal energy transition time t. IC and the nuclear velocity scaling factor f v For each sampled structure, the value of the system's additional internal energy (IEE) is generated randomly and follows a Poisson distribution as follows:
[0114]
[0115] Where P(E) is the probability that the system's extra internal energy IEE equals E, and a, b, and c are calculation parameters. The minimum value of the system's extra internal energy IEE is 0, corresponding to the situation where the electrons still carry a large amount of kinetic energy after ionization, in which case the molecule is ionized without gaining extra internal energy; the maximum value of the system's extra internal energy IEE is E. impact -ε HOMO P(E) is the energy difference between the incident electron and the HOMO level, corresponding to a situation where the kinetic energy of the emitted electron after ionization is 0. This means that all the incident electron energy, except for satisfying the ionization potential of the newly ionized electron, is converted into the kinetic energy of the atomic nucleus. The values of parameters a, b, and c vary with the system, with the goal of maximizing P(E) when the system's extra internal energy IEE is (0.6 eV * number of atoms). The standard mass spectrometry calculation is based on P(E). impact When the voltage is 70 eV, the values of the three parameters are typically approximately 0.2 eV, 1.0 eV, and... Where N el The number of valence electrons in the system.
[0116] Ionized ions are in an excited state within IC time, while ions that have undergone t time after ionization are in an excited state. IC Afterwards, the IEE is completely converted into the kinetic energy of the atomic nucleus. IC The duration depends on the molecular orbital energy and is calculated by the following formula:
[0117]
[0118] Where M is the order number of HOMO, ε i Let α and k be the energies of the i-th molecular orbital. h The constant is 0.5 eV. -1 And 2ps.
[0119] The converted atomic nuclei have non-uniformly scaled velocities. Each atom has a nuclear velocity scaling factor f. v This determines the intensity at which atoms are accelerated. This value is obtained from the following formula:
[0120]
[0121] The extra internal energy (IEE) of each sampling structure is generated randomly, so each architecture has a different core velocity scaling factor.
[0122] Step 3: Based on the AIMD method, starting with 1000 architectures, modify the velocity v = f of each atomic nucleus by the amplification factor. v v0, each structure is simulated for 10 ps under a microcanonical ensemble (NVE) (when t ICWhen the time exceeds 10 ps, the simulation time needs to be extended to ensure that the system's extra internal energy (IEE) is completely converted into the kinetic energy of the atomic nuclei. The ionic products and ionization dissociation paths after electron collision ionization are calculated. Each trajectory is simulated independently, and a single trajectory can provide a clear and specific physical picture of the dissociation path and ionic products.
[0123] Assume that a randomly sampled structure M instantaneously undergoes valence layer ionization to form M + The simulation duration must ensure M + The ions have sufficient time to relax. If ion M + If dissociation occurs within the set simulation time, it is necessary to determine which of the two or more fragment particles produced is the positively charged particle that contributes to the mass spectrum. The specific determination method is as follows:
[0124] S3-1 Calculate the vertical ionization potential VIP of each fragment particle i produced by dissociation. i (Vertical ionization potential):
[0125] VIP i =E scf，i (Q-1)-E scf，i (Q)
[0126] Where Q is the number of electrons when the particle is electrically neutral, and E scf，i (Q) and E scf，i (Q-1) represents the electron energy in the two states before and after ionization.
[0127] S3-2 calculates the statistical charge of each fragment, i.e., the contribution of that fragment to the mass spectrometry, according to the following formula:
[0128]
[0129]
[0130] Among them, C i k is the statistical weight of segment i. B T is the Boltzmann constant. av Let E be the average temperature of the system, and let E be the kinetic energy of the system. kin And the definition of the number of atoms N.
[0131] S3-3 Weight C i Larger fragments are positively charged particles that contribute to the mass spectrum and may undergo further dissociation.
[0132] Step 4 involves statistical analysis of the 1000 calculated MD trajectories to obtain the mass spectrometry results for the target molecule. The large number of trajectories and the fact that randomness was fully considered during sampling ensures the statistical significance of the obtained mass spectra. Adjusting parameters such as the incident electron energy further allows consideration of the influence of different electron energies on the dissociation products.
[0133] like Figure 4 As shown, the method provided in this application embodiment can obtain an ionization and dissociation path of the environmentally friendly gas C4F7N during the kinetic simulation process; as... Figure 5 As shown, the environmentally friendly gas C5F can be obtained. 10 One ionization and dissociation path of O in the kinetic simulation process; such as Figure 6 As shown, according to this application, the environmentally friendly gases C4F7N and C5F can be calculated under standard conditions. 10 The theoretical calculations of O mass spectrometry, compared with experimental results, show high accuracy, verifying the feasibility and accuracy of the calculation method; for example Figure 7 As shown, the environmentally friendly gases C4F7N and C5F can be calculated under different incident electron energies. 10 Theoretical calculations of O mass spectrometry were performed. The calculation results clarified the main ion channels of the two environmentally friendly gases after electron collision ionization and the influence of incident electron energy on this.
[0134] This application provides a computer device according to an embodiment. The computer device of this embodiment includes: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps in the various method embodiments described above. Alternatively, when the processor executes the computer program, it implements the functions of each module / unit in the various device embodiments described above.
[0135] The computer program can be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete this application.
[0136] The computer device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The computer device may include, but is not limited to, a processor and memory.
[0137] The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.
[0138] The memory can be used to store the computer program and / or module, and the processor implements various functions of the computer device by running or executing the computer program and / or module stored in the memory, and by calling the data stored in the memory.
[0139] If the modules / units integrated into the computer device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.
[0140] The above are merely preferred embodiments of this application and are not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.
Claims
1. A method for calculating gas discharge products considering electron collision energy, characterized in that, Includes the following steps: The target molecule was subjected to a thermal bath under a canonical ensemble. After reaching pre-equilibrium, it was simulated under a microcanonical ensemble. The MD trajectory was randomly sampled several times during the simulation period to obtain several system structures and atomic nuclei velocities. Mulliken population analysis was performed on several atomic system architectures and nuclear velocities to obtain the nuclear velocity scaling factor; the specific method is as follows: A single-point energy calculation was performed on several system structures at the PBE0 / def2-SV(P) level to obtain the molecular orbital spectrum at this time. Based on the molecular orbital spectrum and atomic nuclear velocity of the sampled structure, the extra internal energy, internal energy conversion time and nuclear velocity amplification factor of the system were calculated using Mulliken population analysis. The system's additional internal energy The minimum value of is 0, that is The maximum is the energy of the incident electron. and energy level The difference, that is For each sampling structure, The values are all generated randomly and follow a Poisson distribution as follows: in, Additional internal energy for the system equal The probability of; This represents the energy value obtained by the system after the collision. , , The values of these three parameters change with the system, and the goal is to make them equal. exist (0.6eV) The maximum value is taken when the number of atoms is (). The internal energy conversion time as follows: in, for ordinal numbers; and The constant is 0.5 eV. -1 and 2ps; The number of valence electrons in the system; and The first The energy of the first molecular orbital and the first The energy of each molecular orbital; The nuclear velocity amplification factor as follows: in, atomic mass The velocity of the atomic nucleus; Starting with a randomly sampled architecture, the velocities of each atomic nucleus are modified by a nuclear velocity amplification scaling factor. Each architecture is simulated under a microcanonical ensemble to obtain several dissociation paths and physical images of ionic products. By statistically analyzing several dissociation paths and ionic product physical images of several MD trajectories, the mass spectrometry calculation results of the target molecule are obtained.
2. The method for calculating gas discharge products considering electron collision energy according to claim 1, characterized in that, The process of subjecting the target molecule to a thermal bath under a canonical ensemble, achieving pre-equilibrium, and then simulating it under a microcanonical ensemble specifically involves: After 12.5 ps in a 500 K hot bath and reaching pre-equilibrium, the simulation was performed at 25 ps under a microcanonical ensemble.
3. The method for calculating gas discharge products considering electron collision energy according to claim 1 or 2, characterized in that, The target molecule is a gas molecule, a positive ion, or a negative ion.
4. The method for calculating gas discharge products considering electron collision energy according to claim 1, characterized in that, Starting with a randomly sampled architecture, the system modifies the velocities of each atomic nucleus by adjusting the nuclear velocity amplification factor, and simulates each architecture under a microcanonical ensemble to obtain several dissociation paths and physical images of ionic products, including: Amplification factor through nuclear velocity Modify the velocity of each atomic nucleus : Next, each architecture is simulated for a preset time under a microregular ensemble, so that all architectures... Valence layer ionization occurs And within the simulated time period, All ions are capable of relaxation.
5. The method for calculating gas discharge products considering electron collision energy according to claim 1, characterized in that, When simulating each architecture under a microcanonical ensemble, if For ion dissociation, it is necessary to identify the positively charged particles that contribute to the mass spectrum among the two or more fragment particles produced. The specific method is as follows: Calculate the fragment particles produced by each dissociation Vertical ionization potential : in, This represents the number of electrons in a particle when it is electrically neutral. and The electron energies are those of the two states before and after ionization. Calculate the statistical charge of each segment: in, It is a fragment Statistical weights Boltzmann's constant, The average temperature of the system, As the kinetic energy of the system, Number of atoms; weight Larger fragments are positively charged particles that contribute to the mass spectrum.
6. A gas discharge product calculation system considering electron collision energy for implementing the method of claim 1, characterized in that, include: The random sampling module is used to heat the target molecule under a canonical ensemble, and after reaching pre-equilibrium, simulate it under a microcanonical ensemble. It also performs several random samplings on the MD trajectory during the simulation period to obtain several system structures and atomic nuclei velocities. The population analysis module is used to perform Mulliken population analysis on several system architectures and nuclear velocities to obtain the nuclear velocity amplification factor. The path product calculation module is used to simulate each architecture under a microcanonical ensemble by modifying the nuclear velocity of each atom by modifying the nuclear velocity amplification scaling factor, starting from a randomly sampled architecture, and obtaining several dissociation paths and physical images of ionic products. The data statistics module is used to perform statistical analysis on several dissociation paths and ionic product physical images of several MD trajectories to obtain the mass spectrometry calculation results of the target molecule.
7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1-5.
8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1-5.