CN110880357A - Simulation analysis method for SF6 decomposition components based on carbon nano tube and readable storage medium - Google Patents
Simulation analysis method for SF6 decomposition components based on carbon nano tube and readable storage medium Download PDFInfo
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- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 title claims abstract description 34
- 239000002041 carbon nanotube Substances 0.000 title claims abstract description 33
- 229910021393 carbon nanotube Inorganic materials 0.000 title claims abstract description 33
- 238000004088 simulation Methods 0.000 title claims abstract description 31
- 238000000354 decomposition reaction Methods 0.000 title claims abstract description 27
- 238000003860 storage Methods 0.000 title claims abstract description 13
- 238000004458 analytical method Methods 0.000 title claims abstract description 11
- 238000003775 Density Functional Theory Methods 0.000 claims abstract description 42
- 229910018503 SF6 Inorganic materials 0.000 claims abstract description 28
- 238000000034 method Methods 0.000 claims abstract description 28
- SFZCNBIFKDRMGX-UHFFFAOYSA-N sulfur hexafluoride Chemical compound FS(F)(F)(F)(F)F SFZCNBIFKDRMGX-UHFFFAOYSA-N 0.000 claims abstract description 26
- 238000001179 sorption measurement Methods 0.000 claims abstract description 19
- 229960000909 sulfur hexafluoride Drugs 0.000 claims abstract description 18
- 238000004364 calculation method Methods 0.000 claims description 17
- 238000005284 basis set Methods 0.000 claims description 11
- 239000000463 material Substances 0.000 claims description 7
- 238000005457 optimization Methods 0.000 claims description 7
- 238000006073 displacement reaction Methods 0.000 claims description 4
- 230000010287 polarization Effects 0.000 claims description 4
- 238000012546 transfer Methods 0.000 claims description 3
- 238000002474 experimental method Methods 0.000 abstract description 7
- 230000006870 function Effects 0.000 description 25
- 239000007789 gas Substances 0.000 description 25
- 238000010586 diagram Methods 0.000 description 9
- 238000004590 computer program Methods 0.000 description 7
- 238000009413 insulation Methods 0.000 description 4
- 230000008569 process Effects 0.000 description 4
- 238000012545 processing Methods 0.000 description 4
- 230000007547 defect Effects 0.000 description 3
- 229910052731 fluorine Inorganic materials 0.000 description 3
- 239000011737 fluorine Substances 0.000 description 3
- YCKRFDGAMUMZLT-UHFFFAOYSA-N Fluorine atom Chemical compound [F] YCKRFDGAMUMZLT-UHFFFAOYSA-N 0.000 description 2
- NINIDFKCEFEMDL-UHFFFAOYSA-N Sulfur Chemical compound [S] NINIDFKCEFEMDL-UHFFFAOYSA-N 0.000 description 2
- 238000006243 chemical reaction Methods 0.000 description 2
- 239000000126 substance Substances 0.000 description 2
- 229910052717 sulfur Inorganic materials 0.000 description 2
- 239000011593 sulfur Substances 0.000 description 2
- 230000005428 wave function Effects 0.000 description 2
- UCKMPCXJQFINFW-UHFFFAOYSA-N Sulphide Chemical compound [S-2] UCKMPCXJQFINFW-UHFFFAOYSA-N 0.000 description 1
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 229910052799 carbon Inorganic materials 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000002485 combustion reaction Methods 0.000 description 1
- 150000001875 compounds Chemical class 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 230000005684 electric field Effects 0.000 description 1
- 230000001747 exhibiting effect Effects 0.000 description 1
- 230000002349 favourable effect Effects 0.000 description 1
- 230000005283 ground state Effects 0.000 description 1
- 239000011261 inert gas Substances 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000009965 odorless effect Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 229910052760 oxygen Inorganic materials 0.000 description 1
- 239000001301 oxygen Substances 0.000 description 1
- 150000003856 quaternary ammonium compounds Chemical class 0.000 description 1
- OBTWBSRJZRCYQV-UHFFFAOYSA-N sulfuryl difluoride Chemical compound FS(F)(=O)=O OBTWBSRJZRCYQV-UHFFFAOYSA-N 0.000 description 1
- 230000009967 tasteless effect Effects 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
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Abstract
The invention discloses a simulation analysis method of SF6 decomposition components based on carbon nano tubes and a readable storage medium, wherein the method comprises the following steps: constructing a corresponding molecular structure according to molecular formulas of the sulfur hexafluoride gas decomposition product and the carbon nano tube; selecting a density functional theory DFT function and a corresponding base group; optimizing the molecular structure according to the selected DFT function and the selected basis group; and performing adsorption simulation according to the optimized molecular structure. The method optimizes the molecular structure according to the selected DFT function and the selected basis group; adsorption simulation is carried out according to the optimized molecular structure, the gas-sensitive characteristic of the carbon nano tube on sulfur hexafluoride decomposition components is obtained through theoretical simulation, and guidance is provided for practical experiments.
Description
Technical Field
The invention relates to the technical field of gas insulated switchgear, in particular to a simulation analysis method of SF6 decomposition components based on carbon nano tubes and a readable storage medium.
Background
Sulfur hexafluoride (SF)6) The gas has been known for centuries and is an inert gas, SF, synthesized by the combustion of sulfur in fluorine gas by the French chemist Morson (Moissan) and Lebeau (Lebeau)6Pure SF with stable chemical property at room temperature6The gas is tasteless, odorless and non-combustible. SF6MoleculeIn the case of the (C), six fluorine (F) atoms are arranged in a fully symmetrical octahedral arrangement around a central sulfur (S) atom. SF6Gas is widely used in Gas Insulated Switchgear (GIS) because of its excellent insulating and arc extinguishing properties. Long-term operational experience has shown that Partial Discharges (PDs) occur to different degrees inside a GIS device due to inherent defects or some new insulation problems, and these defects are further developed along with the increase of the operation time, and may eventually cause serious GIS device insulation problems, resulting in irreparable loss. When partial discharge continues, the energy generated by the discharge is such that SF6Decomposition to SF4、SF3、SF2And (3) further reacting part of the low-fluorine sulfide with trace water and oxygen existing in the GIS equipment to finally generate SO2F2、SOF2And SO2And (c) a compound such as a quaternary ammonium compound. The gas-sensitive change caused by the gas on the gas-sensitive material can reflect the insulation condition of the device.
Carbon nanotubes have been considered as the most promising material for gas detection because of their unique structure exhibiting excellent physical and chemical properties. The potential of the simulation method applied to the electrical field is effectively explored by means of the simulation method, favorable support and guidance are provided for engineering practice, and time is saved compared with experiments.
Disclosure of Invention
In view of the above-mentioned defects of the prior art, the present invention aims to provide a simulation analysis method for SF6 decomposition components based on carbon nanotubes and a readable storage medium, which theoretically simulates the gas-sensitive characteristics of carbon nanotubes to sulfur hexafluoride decomposition components and provides guidance for practical experiments.
One of the purposes of the invention is realized by the technical scheme that the simulation analysis method of the SF6 decomposition component based on the carbon nano tube comprises the following steps:
constructing a corresponding molecular structure according to molecular formulas of the sulfur hexafluoride gas decomposition product and the carbon nano tube;
selecting a density functional theory DFT function and a corresponding base group;
optimizing the molecular structure according to the selected DFT function and the selected basis group;
and performing adsorption simulation according to the optimized molecular structure.
Optionally, the DFT function is a generalized gradient approximation GGA-PBE functional;
selecting a density functional theory DFT function and a corresponding base group, wherein the density functional theory DFT function comprises the following steps:
and selecting a GGA-PBE functional and performing electronic pseudopotential calculation by adopting a bivariate orbit basis set + p orbit polarization function DNP.
Optionally, optimizing the molecular structure according to the selected DFT function and basis set includes:
energy convergence accuracy, maximum stress and maximum displacement are set.
Optionally, after the molecular structure is optimized according to the selected DFT function and the basis set, the method further includes:
and performing frequency calculation based on the optimized molecular structure, and repeating the optimization under the condition that the frequency calculation result has virtual frequency.
Optionally, performing adsorption simulation according to the optimized molecular structure, including:
and placing the optimized molecular structure close to the carbon nano tube, and performing adsorption simulation under the same parameters.
Optionally, constructing a corresponding molecular structure according to the molecular formula of the sulfur hexafluoride gas decomposition product and the carbon nanotube, including:
and constructing a corresponding molecular structure through a material calculation platform according to the molecular formulas of the sulfur hexafluoride gas decomposition product and the carbon nano tube.
The second object of the present invention is achieved by the technical solution, which is a computer-readable storage medium, wherein an implementation program for information transfer is stored on the computer-readable storage medium, and the implementation program implements the steps of the foregoing method when executed by a processor.
Due to the adoption of the technical scheme, the invention has the following advantages: optimizing the molecular structure according to the selected DFT function and the selected basis group; adsorption simulation is carried out according to the optimized molecular structure, the gas-sensitive characteristic of the carbon nano tube on sulfur hexafluoride decomposition components is obtained through theoretical simulation, and guidance is provided for practical experiments.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention.
Drawings
The drawings of the invention are illustrated as follows:
FIG. 1 is a flow chart of a method according to an embodiment of the present invention;
Detailed Description
The invention is further illustrated by the following figures and examples.
Example one
A first embodiment of the present invention provides a simulation analysis method for SF6 decomposition components based on carbon nanotubes, as shown in fig. 1, the method includes the following steps:
constructing a corresponding molecular structure according to molecular formulas of the sulfur hexafluoride gas decomposition product and the carbon nano tube;
selecting a density functional theory DFT function and a corresponding base group;
optimizing the molecular structure according to the selected DFT function and the selected basis group;
and performing adsorption simulation according to the optimized molecular structure.
Optionally, constructing a corresponding molecular structure according to the molecular formula of the sulfur hexafluoride gas decomposition product and the carbon nanotube, including:
and constructing a corresponding molecular structure through a material calculation platform according to the molecular formulas of the sulfur hexafluoride gas decomposition product and the carbon nano tube.
Specifically, in this example, the molecular structure was initially constructed: at the GUI interface of the materials laboratory platform (MS), the corresponding molecular structure is constructed according to the molecular formula of the decomposition product and the carbon nanotube.
Optimizing the molecular structure according to the selected DFT function and the selected basis group; adsorption simulation is carried out according to the optimized molecular structure, the gas-sensitive characteristic of the carbon nano tube on sulfur hexafluoride decomposition components is obtained through theoretical simulation, and guidance is provided for practical experiments.
Optionally, the DFT function is a generalized gradient approximation GGA-PBE functional;
selecting a density functional theory DFT function and a corresponding base group, wherein the density functional theory DFT function comprises the following steps:
and selecting a GGA-PBE functional and performing electronic pseudopotential calculation by adopting a bivariate orbit basis set + p orbit polarization function DNP.
Specifically, in this embodiment, the selection of the DFT functional: the Hohenberg-Kohn theorem concludes that the ground state energy in schrodinger's equation is a function of electron density, but the form of the function is not. Therefore, in this embodiment, selecting an appropriate DFT functional to describe the correlation exchange energy between electrons is the first step of accurately describing and researching the reaction system, and in this embodiment, the GGA-PBE is used to process the exchange correlation energy.
Selection of the base group: the basis set is a wave function used to spread the electrons in the density functional calculation. Therefore, the larger the size of the basis set is, the greater the degree of freedom of the unfolded wave function is, and the density functional theory is a variation theory, and the greater the degree of freedom means the more correct theory. In this embodiment, an electronic pseudopotential is calculated by using a bivariate orbital basis group + p-orbital polarization function (DNP).
Optionally, optimizing the molecular structure according to the selected DFT function and basis set includes:
energy convergence accuracy, maximum stress and maximum displacement are set.
Specifically, the molecular structure is optimized: on the basis of the DFT method and the selection of the basis group, when the structure of the molecule is optimized, in the optimization process, a software program can continuously calculate different molecular structures, and the energy convergence precision, the maximum stress and the displacement are respectively set to be 10-5Ha，
And
and stopping the calculation if the convergence condition is met.
Optionally, after the molecular structure is optimized according to the selected DFT function and the basis set, the method further includes:
and performing frequency calculation based on the optimized molecular structure, and repeating the optimization under the condition that the frequency calculation result has virtual frequency.
Specifically, after the structure optimization is completed, frequency calculation is further performed in this embodiment to check whether the virtual frequency exists, and if the virtual frequency exists, the optimization is not accurate, and the optimization needs to be continued.
Optionally, performing adsorption simulation according to the optimized molecular structure, including:
and placing the optimized molecular structure close to the carbon nano tube, and performing adsorption simulation under the same parameters.
Specifically, in this embodiment, the adsorption simulation is performed, and includes: and placing the optimized gas molecules at a position close to the carbon nano tube, and performing adsorption simulation under the condition of the same parameter selection.
Then, a mechanism analysis is carried out: and analyzing an electron state density diagram, charge distribution, energy band structure and reaction energy of different adsorption conditions.
In conclusion, the method provided by the invention is used for carrying out simulation analysis on the adsorption behavior of the sulfur hexafluoride gas decomposition component on the carbon nano tube based on the density functional theory. The molecular structure of a typical decomposition product of sulfur hexafluoride is constructed in a material laboratory platform (MS), the structure is optimized based on a GGA-PBE method in a density functional theory, molecular energy is obtained through energy calculation, and carbon nano tubes are optimized through the method. And placing the optimized gas molecules at a position close to the carbon nano-meter for simulation calculation and simulation of the adsorption process. The analysis lays a theoretical foundation for applying the carbon nano tube to the online monitoring of the gas insulation equipment.
The method of the invention has the following advantages:
1. because the period of the actual experiment is long, the method can theoretically simulate the gas-sensitive characteristic of the carbon nano tube to the sulfur hexafluoride decomposition component, and provides guidance for the actual experiment.
2. The adsorption condition of the product gas molecules on the surface of the carbon nano tube can be decomposed from a microscopic level.
The second object of the present invention is achieved by the technical solution, which is a computer-readable storage medium, wherein an implementation program for information transfer is stored on the computer-readable storage medium, and the implementation program implements the steps of the foregoing method when executed by a processor.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered thereby.
Claims (7)
1. A simulation analysis method for SF6 decomposition components based on carbon nano tubes is characterized by comprising the following steps:
constructing a corresponding molecular structure according to molecular formulas of the sulfur hexafluoride gas decomposition product and the carbon nano tube;
selecting a density functional theory DFT function and a corresponding base group;
optimizing the molecular structure according to the selected DFT function and the selected basis group;
and performing adsorption simulation according to the optimized molecular structure.
2. The method of claim 1, wherein the DFT function is a generalized gradient approximation GGA-PBE functional;
selecting a density functional theory DFT function and a corresponding base group, wherein the density functional theory DFT function comprises the following steps:
and selecting a GGA-PBE functional and performing electronic pseudopotential calculation by adopting a bivariate orbit basis set + p orbit polarization function DNP.
3. The method of claim 2, wherein optimizing the molecular structure based on the selected DFT function and basis set comprises:
energy convergence accuracy, maximum stress and maximum displacement are set.
4. The method of claim 3, wherein after optimizing the molecular structure according to the selected DFT function and basis set, the method further comprises:
and performing frequency calculation based on the optimized molecular structure, and repeating the optimization under the condition that the frequency calculation result has virtual frequency.
5. The method of claim 4, wherein performing adsorption simulations based on the optimized molecular structure comprises:
and placing the optimized molecular structure close to the carbon nano tube, and performing adsorption simulation under the same parameters.
6. The method of claim 1, wherein constructing the corresponding molecular structure from sulfur hexafluoride gas decomposition products and carbon nanotube molecular formulas comprises:
and constructing a corresponding molecular structure through a material calculation platform according to the molecular formulas of the sulfur hexafluoride gas decomposition product and the carbon nano tube.
7. A computer-readable storage medium, characterized in that it has stored thereon a program for implementing the transfer of information, which program, when being executed by a processor, implements the steps of the method according to any one of claims 1 to 6.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112014440A (en) * | 2020-09-04 | 2020-12-01 | 西南大学 | Preparation method and application of platinum nitrogen doped CNT (carbon nanotube) and doped CNT sensor |
| CN113299356A (en) * | 2021-05-31 | 2021-08-24 | 国网山东省电力公司电力科学研究院 | Carbon-doped boron nitride nanotube pairs SF6/N2Calculation method and system for adsorption of decomposition products |
| CN114324773A (en) * | 2022-01-07 | 2022-04-12 | 国家电网有限公司 | Metal modified MoSe applied to switch cabinet discharge decomposition component2Method for analyzing adsorption performance |
| CN114817843A (en) * | 2022-06-29 | 2022-07-29 | 武汉高德红外股份有限公司 | Energy band structure calculation method of superlattice infrared detection material |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104330371A (en) * | 2014-11-04 | 2015-02-04 | 中国石油大学(华东) | Method for quantitative analysis of photocatalytic performance of silver bromide cluster |
| CN105718719A (en) * | 2016-01-14 | 2016-06-29 | 中国石油大学(华东) | Simulation method for optimizing molecular structure of biosurfactant |
| CN108256280A (en) * | 2018-03-22 | 2018-07-06 | 华南师范大学 | Verify method of the nickel doping minor radius carbon nanotube to the adsorption capacity of sulfur dioxide |
| CN109599151A (en) * | 2018-11-30 | 2019-04-09 | 武汉大学 | A kind of perfluoroketone environment-friendly type substitution aerothermodynami emulation mode |
-
2019
- 2019-11-21 CN CN201911148253.2A patent/CN110880357A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104330371A (en) * | 2014-11-04 | 2015-02-04 | 中国石油大学(华东) | Method for quantitative analysis of photocatalytic performance of silver bromide cluster |
| CN105718719A (en) * | 2016-01-14 | 2016-06-29 | 中国石油大学(华东) | Simulation method for optimizing molecular structure of biosurfactant |
| CN108256280A (en) * | 2018-03-22 | 2018-07-06 | 华南师范大学 | Verify method of the nickel doping minor radius carbon nanotube to the adsorption capacity of sulfur dioxide |
| CN109599151A (en) * | 2018-11-30 | 2019-04-09 | 武汉大学 | A kind of perfluoroketone environment-friendly type substitution aerothermodynami emulation mode |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112014440A (en) * | 2020-09-04 | 2020-12-01 | 西南大学 | Preparation method and application of platinum nitrogen doped CNT (carbon nanotube) and doped CNT sensor |
| CN112014440B (en) * | 2020-09-04 | 2022-02-01 | 西南大学 | Preparation method and application of platinum nitrogen doped CNT (carbon nanotube) and doped CNT sensor |
| CN113299356A (en) * | 2021-05-31 | 2021-08-24 | 国网山东省电力公司电力科学研究院 | Carbon-doped boron nitride nanotube pairs SF6/N2Calculation method and system for adsorption of decomposition products |
| CN114324773A (en) * | 2022-01-07 | 2022-04-12 | 国家电网有限公司 | Metal modified MoSe applied to switch cabinet discharge decomposition component2Method for analyzing adsorption performance |
| CN114817843A (en) * | 2022-06-29 | 2022-07-29 | 武汉高德红外股份有限公司 | Energy band structure calculation method of superlattice infrared detection material |
| CN114817843B (en) * | 2022-06-29 | 2022-11-04 | 武汉高德红外股份有限公司 | Energy band structure calculation method of superlattice infrared detection material |
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Application publication date: 20200313 |