CN110517733B - Method for constructing dissipative particle dynamic force field - Google Patents

Method for constructing dissipative particle dynamic force field Download PDF

Info

Publication number
CN110517733B
CN110517733B CN201910859103.6A CN201910859103A CN110517733B CN 110517733 B CN110517733 B CN 110517733B CN 201910859103 A CN201910859103 A CN 201910859103A CN 110517733 B CN110517733 B CN 110517733B
Authority
CN
China
Prior art keywords
beads
surfactant
dpd
coarse
interaction force
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201910859103.6A
Other languages
Chinese (zh)
Other versions
CN110517733A (en
Inventor
麦兆环
桂双林
熊继海
吴九九
付嘉琦
闫冰
易其臻
张苗辉
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
ENERGY RESEARCH INSTITUTE OF JIANGXI ACADEMY OF SCIENCES
Original Assignee
ENERGY RESEARCH INSTITUTE OF JIANGXI ACADEMY OF SCIENCES
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by ENERGY RESEARCH INSTITUTE OF JIANGXI ACADEMY OF SCIENCES filed Critical ENERGY RESEARCH INSTITUTE OF JIANGXI ACADEMY OF SCIENCES
Priority to CN201910859103.6A priority Critical patent/CN110517733B/en
Publication of CN110517733A publication Critical patent/CN110517733A/en
Application granted granted Critical
Publication of CN110517733B publication Critical patent/CN110517733B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16CCOMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
    • G16C10/00Computational theoretical chemistry, i.e. ICT specially adapted for theoretical aspects of quantum chemistry, molecular mechanics, molecular dynamics or the like

Abstract

The invention belongs to the field of environmental pollution treatment, and particularly relates to a construction method for simulating a dynamic force field of a dissipative particle of a surfactant solution by using a computer. The method comprises the following steps: 1) establishing a coarse graining model of a surfactant and water molecules; 2) calculating an interaction force parameter between each coarse grained bead by using a Dissipative Particle Dynamics (DPD) theory; 3) establishing a coarse grained structure model of a solution system consisting of a surfactant and water by using Materials Studio software; 4) performing dissipative particle dynamics simulation on the parameters and models obtained in the step (2) and the step (3) by using a DPD module in Materials Studio software to obtain corresponding microstructure property parameters of the surfactant solution; 5) and adjusting interaction parameters among the coarse-grained beads, and optimizing by combining with experimental data of microstructure properties of the surfactant solution to obtain a DPD force field which can be matched with experimental results. The construction method of the invention improves the precision of the coarse grained power field, promotes the development of the coarse grained power field, and has important guiding significance for researching the physicochemical properties of the surfactant in the solution and at the interface.

Description

Method for constructing dissipative particle dynamic force field
Technical Field
The invention belongs to the field of environmental pollution treatment, and particularly relates to a construction method for simulating a dynamic force field of a dissipative particle of a surfactant solution by using a computer.
Background
The surfactant is a molecule with hydrophilic and lipophilic groups, has a series of physical and chemical properties of wetting or anti-sticking, emulsifying, air bubble or defoaming, solubilization, dispersion, washing, anticorrosion, antistatic and the like, and is widely applied to daily life and industrial production. However, in the using process, a large amount of wastewater and waste residues containing the surfactant are inevitably discharged into water, soil and other environments, so that serious harm is caused to human bodies and environmental ecosystems, and the problem of environmental pollution is also getting more serious. Therefore, the treatment of industrial and agricultural production and domestic wastewater containing the surfactant is particularly urgent. At present, the treatment of surfactant wastewater has become a research hotspot, and the research on the physicochemical properties of the surfactant in an aqueous solution and at an interface has a main guiding significance.
In the process of diffusion, aggregation and clustering of the surfactant in the aqueous solution, the dynamic change of the structure and the morphology of the system is difficult to directly observe by using the traditional experimental characterization method (such as SEM, TEM, AFM and the like). Computer simulation is a powerful means for studying surface phenomena such as adsorption and diffusion. Molecular or mesoscopic simulations allow for the microscopic investigation of the structure and properties of a substance and directly provide data that cannot be experimentally obtained under extreme conditions. How to accurately explore the interaction force fields between surfactant molecules and between the surfactant molecules and water molecules from a microscopic angle by using a DPD simulation method so as to represent the microscopic properties of a surfactant solution, and the method has important significance for researching the physical and chemical properties of a surfactant system and the application of the surfactant system in the fields of chemistry and chemical industry, biology, medicine and the like.
Disclosure of Invention
Aiming at the problem that the development method of the force field related to the surfactant solution system in the prior art is blindly provided, the invention provides an optimized development method of the force field for researching the interaction force of the surfactant solution system, so as to improve the precision of the coarse grained force field and promote the development of the coarse grained force field.
A method for developing a dissipative particle dynamic force field of a surfactant solution comprises the following steps:
(1) establishing a coarse granulation model of surfactant molecules and water molecules in Materials Studio software;
(2) calculating interaction force parameters among the coarse grained beads in the coarse grained model in the step (1) to obtain corresponding interaction force parameter ranges;
(3) constructing a coarse granulation model of the surfactant solution in Materials Studio software;
(4) and (3) obtaining parameters and models in the step (2) and the step (3), performing dissipative particle dynamics simulation by using a DPD module in Materials Studio software, recording coordinates and motion tracks of the coarse-grained beads after the system reaches balance, analyzing bond length and interaction energy among the beads according to an Analysis function in the DPD module, directly observing the dynamic change process of the structure and the morphology of a simulation system by combining with Animation in the Materials Studio software, and obtaining corresponding microstructure property parameters of the surfactant solution.
(5) Repeatedly fine-tuning the interaction force parameters among the beads in the numerical range of the interaction force parameter range table to obtain microstructure property parameter simulation values of the surfactant solution under the interaction forces with different strengths; and comparing the simulation value with corresponding experimental data until the simulation value is consistent with the experimental data, and determining that the interaction force parameter under the condition is the optimized DPD force field parameter of the surfactant solution.
Further, the coarse grain model established in step (1) is as follows: water bead W is 3H2O, the surfactant molecule is HnTmConsists of n hydrophilic beads H and m hydrophobic beads T.
Further, the surfactant is sodium alkyl sulfonate containing sulfonic acid groups.
Further, the calculation formula of the interaction parameter between the coarse grained beads in the step (2) is as follows:
Figure BDA0002199182100000021
Figure BDA0002199182100000022
wherein, aiiRepresents the interaction force parameter between identical DPD beads;
aijrepresents the interaction force parameter between different DPD beads;
in the formula, NmRepresents the level of coarsening in the DPD simulation, i.e., the number of water molecules contained in one DPD bead;
kBt represents an energy unit in the DPD simulation;
ρ represents the density of the DPD simulation system;
χijrepresents the Flory-Huggins parameter between different DPD beads.
Further, the parameters of the interaction force between the beads obtained in the step (2) are as follows: the parameter range of the interaction force of the water beads W and the hydrophilic beads H is 65-75.8; the interaction force parameter range of the water beads W and the hydrophobic beads T is 90-104; the interaction force parameter range between the hydrophilic bead H and the hydrophobic bead T is 84-124, the interaction force parameter between the water beads W is 78, the interaction force parameter between the hydrophobic beads T is 78, and the interaction force parameter between the hydrophilic bead H is 86.7.
Further, the coarse grained model in the step (3) is constructed by a DPD module in Materials Studio software, and a cube box with a system of x ═ y ═ z coordinates is adopted, and water beads W and surfactant molecules HnTm are added into the box, wherein the number of the water beads and the surfactant molecules is converted according to the concentration of the surfactant.
Further, the specific parameters of the DPD dynamics simulation in step (4) are set as follows: the total simulation time is 200000 steps, the temperature is set to 298K, the time step is set to 0.05, and one simulation result is output every 1000 steps.
Further, the microstructure property parameters of the surfactant in the steps (4) and (5) comprise one or more of a sub-aggregation number, a critical micelle concentration and an aggregation morphology.
Further, the experimental data in the step (5) is the critical micelle concentration, the number of sub-aggregates or the micelle aggregation morphology obtained by experiments in the references.
The invention has the advantages and positive effects that: compared with the prior development, the invention provides a method for establishing and optimizing microstructure properties based on the surfactant by utilizing a dissipative particle dynamics simulation technology, improves the precision of a coarse graining force field, expands the application of the coarse graining force field, and has important guiding significance for researching the physicochemical properties of the surfactant in the solution and at an interface.
Drawings
FIG. 1 shows a coarse water molecule granulation model constructed in Materials Studio software;
FIG. 2 shows a coarse granulation model H1T2 of sodium hexaalkyl sulfonate molecules constructed in Materials Studio software;
FIG. 3 shows a coarse granulation model H1T3 of sodium nonaalkylsulfonate molecules constructed in Materials Studio software;
FIG. 4 shows a coarse granulation model H1T4 of sodium dodecyl sulfate molecules constructed in Materials Studio software;
FIG. 5 shows a coarse particle size model H1T5 of sodium pentadecylsulfonate molecules constructed in Materials Studio software;
FIG. 6. aggregation morphology of surfactant H1T2 solution in equilibrium obtained under parametric conditions.
Detailed Description
For better understanding of the present invention, the technical solutions of the present invention will be described in further detail with reference to specific embodiments, but the scope of the present invention is not limited to the scope shown in the examples.
Example (b):
(1) in this example, surfactant molecules represented by sodium alkylsulfonate are selected, and a coarse grained model of the surfactant molecules and water molecules is first established, that is, coarse grained DPD beads are defined as follows: water bead W (3H)2O) the coarse grain model is shown in FIG. 1; according to the structure of sodium alkylsulfonate, the surfactant molecule consists of n hydrophilic beads H (-OSO)3Na) and m hydrophobic beads T (end CH)3-CH2-CH2-or a middle-CH2-CH2-CH2-) composition (DPD coarse grained models of sodium hexaalkylsulfonate, sodium nonaalkylsulfonate, sodium dodecylsulfonate, sodium pentadecylsulfonate are represented as H1T2, H1T3, H1T4, H1T5, respectively), and DPD coarse grained structural models thereof are shown in FIGS. 2 to 5.
(2) Calculating interaction force parameters among the coarse-grained beads in the coarse-grained model in the step (1) to obtain corresponding interaction force parameter ranges, and calculating the interaction force parameters among the coarse-grained beads according to Flory-Huggins parameters of the beads, wherein the calculation formula is as follows;
Figure BDA0002199182100000031
Figure BDA0002199182100000041
wherein, aiiRepresents the interaction force parameter between identical DPD beads;
aijrepresents the interaction force parameter between different DPD beads;
in the formula, NmRepresents the level of coarse grain in the DPD simulation, namely: the number of water molecules contained in one DPD bead;
kBt represents an energy unit in the DPD simulation;
ρ represents the density of the DPD analog system, where ρ is 3;
χijthe Flory-Huggins parameters between different DPD beads are shown and obtained in the reference.
The calculated interaction force parameters are shown in the table below.
aij/aii H T W
H 86.7
T 84-124 78
W 65-75.8 90-104 78
Wherein, aHTRepresenting the interaction force between hydrophilic groups and hydrophobic groups of the surfactant, ranging from 84 to 124; a isWHShowing the interaction force between the water beads and the hydrophilic group beads of the surfactant,the range is 65-75.8; a isWTRepresenting the interaction force between the water beads and the hydrophobic base beads of the surfactant, ranging from 90 to 104.
(3) The coarse grained structure model of the surfactant solution was constructed in the DPD module in Materials Studio software as follows: and a cubic box with system coordinates of x, y, z and 20, wherein water beads W and surfactant molecules H1Tm (m is 2,3,4 and 5) are added into the box, and the number of the water beads and the surfactant molecules is converted according to the concentration of the surfactant.
(4) Performing dissipative particle dynamics simulation on the established surfactant solution coarse granulation model and the obtained force field parameters by using a DPD module in the materials studio software, wherein the specific parameters of the DPD dynamics simulation are set as follows: the total simulation time is 200000 steps, the temperature is set to 298K, the time step is set to 0.05, and one simulation result is output every 1000 steps. After the system is balanced, the coordinates and the motion trail of each coarse-grained bead are recorded, the bond length and the interaction energy among the beads are analyzed according to the Analysis function in the DPD module, the dynamic change process of the structure and the morphology of the simulation system is directly observed by combining with Animation in material Studio software, and corresponding microstructure property parameters of the surfactant solution are obtained.
(5) Adjusting the interaction strength between the surfactant and water according to the parameters among the beads in the table 1 to obtain microstructure property parameter simulation values of the surfactant solution under the interaction forces with different strengths; and comparing the simulation value with the experimental data until the simulation value is consistent with the experimental data, and determining that the interaction force parameter under the condition is the optimized DPD force field parameter of the surfactant solution. The aggregation morphology of the H1T2 solution system after the system reaches the equilibrium state under the optimized parameter conditions is shown in FIG. 6, wherein the black beads represent H and the white beads represent T.
Although the preferred embodiments of the present patent have been described in detail, the present patent is not limited to the above embodiments, and various changes can be made without departing from the spirit of the present patent within the knowledge of those skilled in the art.

Claims (8)

1. A method for constructing a dynamic force field of a dissipative particle of a surfactant solution is characterized by comprising the following steps: the method comprises the following steps:
(1) establishing a coarse granulation model of surfactant molecules and water molecules in Materials Studio software;
(2) calculating interaction force parameters among the coarse grained beads in the coarse grained model in the step (1) to obtain corresponding interaction force parameter ranges, wherein the calculation formula of the interaction force parameters among the coarse grained beads is as follows;
Figure FDA0002390425640000011
Figure FDA0002390425640000012
wherein: a isiiRepresents the interaction force parameter between identical DPD beads;
aijrepresents the interaction force parameter between different DPD beads;
in the formula: n is a radical ofmRepresents the level of coarse grain in the DPD simulation, namely: the number of water molecules contained in one DPD bead;
kBt represents an energy unit in the DPD simulation;
ρ represents the density of the DPD simulation system;
χijrepresents Flory-Huggins parameters among different DPD beads;
(3) constructing a coarse granulation model of the surfactant solution in Materials Studio software;
(4) obtaining parameters and models in the step (2) and the step (3), performing dissipative particle dynamics simulation by using a DPD module in Materials Studio software, recording coordinates and motion tracks of the coarse-grained beads after the system reaches balance, analyzing bond length and interaction energy among the beads according to an Analysis function in the DPD module, directly observing a dynamic change process of the structure and the morphology of a simulation system by combining with Animation in the Materials Studio software, and obtaining corresponding microstructure property parameters of a surfactant solution;
(5) repeatedly fine-tuning the interaction force parameters among the beads in the numerical range of the interaction force parameter range table to obtain microstructure property parameter simulation values of the surfactant solution under the interaction forces with different strengths; and comparing the simulation value with corresponding experimental data until the simulation value is consistent with the experimental data, and determining that the interaction force parameter under the condition is the optimized DPD force field parameter of the surfactant solution.
2. The method of claim 1, wherein the method comprises the steps of: the coarse grain model established in the step (1) is as follows: the water beads W are 3H2O, the surfactant molecules are HnTm and consist of n hydrophilic beads H and m hydrophobic beads T.
3. The method of claim 1, wherein the method comprises the steps of: the surfactant is sodium alkyl sulfonate containing sulfonic acid groups.
4. The method of claim 3, wherein the method comprises the steps of: the parameter range of the interaction force among the beads obtained in the step (2) is as follows: the parameter range of the interaction force of the water beads W and the hydrophilic beads H is 65-75.8; the interaction force parameter range of the water beads W and the hydrophobic beads T is 90-104; the interaction force parameter range between the hydrophilic bead H and the hydrophobic bead T is 84-124, the interaction force parameter between the water beads W is 78, the interaction force parameter between the hydrophobic beads T is 78, and the interaction force parameter between the hydrophilic bead H is 86.7.
5. The method of claim 1, wherein the method comprises the steps of: the coarse graining model in the step (3) is constructed through a DPD module in Materials Studio software, a cube box with a system of x, y, z coordinates is adopted, water beads W and surfactant molecules HnTm are added into the box, and the quantity of the water beads and the surfactant molecules is converted according to the concentration of the surfactant.
6. The method of claim 1, wherein the method comprises the steps of: the specific parameters of the DPD dynamics simulation in step (4) are set as follows: the total simulation time is 200000 steps, the temperature is set to 298K, the time step is set to 0.05, and one simulation result is output every 1000 steps.
7. The method for constructing the dynamic force field for dissipating the particles from the surfactant solution according to claim 1, wherein the microstructure property parameters of the surfactant in the steps (4) and (5) comprise one or more of a sub-aggregation number, a critical micelle concentration and an aggregation morphology.
8. The method for constructing the dynamic force field for dissipating the particles from the surfactant solution according to claim 1, wherein the experimental data in the step (5) is the critical micelle concentration, the sub-aggregation number or the micelle aggregation morphology obtained by experiments in the literature.
CN201910859103.6A 2019-09-11 2019-09-11 Method for constructing dissipative particle dynamic force field Active CN110517733B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201910859103.6A CN110517733B (en) 2019-09-11 2019-09-11 Method for constructing dissipative particle dynamic force field

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910859103.6A CN110517733B (en) 2019-09-11 2019-09-11 Method for constructing dissipative particle dynamic force field

Publications (2)

Publication Number Publication Date
CN110517733A CN110517733A (en) 2019-11-29
CN110517733B true CN110517733B (en) 2020-05-08

Family

ID=68630662

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201910859103.6A Active CN110517733B (en) 2019-09-11 2019-09-11 Method for constructing dissipative particle dynamic force field

Country Status (1)

Country Link
CN (1) CN110517733B (en)

Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111272612B (en) * 2020-03-03 2022-01-28 西南石油大学 Primary screening method of demulsifier
CN111739589B (en) * 2020-06-29 2022-07-05 青岛科技大学 Mesoscale-based simulation method for dissolving lignin by eutectic solvent
CN112216349A (en) * 2020-10-13 2021-01-12 中国民航大学 Method for constructing rigid asphaltene molecular structure in dissipative particle dynamics simulation
CN113223624B (en) * 2021-02-05 2023-04-28 中南大学 Cross-scale simulation method for predicting microstructure evolution in colloid shearing motion process

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2720163A1 (en) * 2012-10-12 2014-04-16 Steinbeis Advanced Risk Technologies GmbH Method for estimating corrosion self-healing and corresponding computer system
CN104156494A (en) * 2013-05-15 2014-11-19 中国科学院化学研究所 Method for constructing rigid Janus nano particle for dissipation particle dynamics (DPD) simulation
CN104573223A (en) * 2015-01-04 2015-04-29 中国石油大学(华东) Oil-water-solid three-phase system coarse graining force field development method
CN105095627A (en) * 2014-05-15 2015-11-25 中国科学院化学研究所 Model construction method for coarse-grained molecular dynamics study on water-surfactant-liquid crystal three-phase mixed system

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104156495A (en) * 2013-05-15 2014-11-19 中国科学院化学研究所 Method for establishing T-shaped, pi-shaped and swallow-tail-shaped three-component parents molecule coarse graining model on mesoscale
CN110070918B (en) * 2019-04-02 2022-12-27 重庆邮电大学 Coarse graining method based on intermolecular interaction

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2720163A1 (en) * 2012-10-12 2014-04-16 Steinbeis Advanced Risk Technologies GmbH Method for estimating corrosion self-healing and corresponding computer system
CN104156494A (en) * 2013-05-15 2014-11-19 中国科学院化学研究所 Method for constructing rigid Janus nano particle for dissipation particle dynamics (DPD) simulation
CN105095627A (en) * 2014-05-15 2015-11-25 中国科学院化学研究所 Model construction method for coarse-grained molecular dynamics study on water-surfactant-liquid crystal three-phase mixed system
CN104573223A (en) * 2015-01-04 2015-04-29 中国石油大学(华东) Oil-water-solid three-phase system coarse graining force field development method

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
《Electronic Structure and Mesoscopic Simulations of Nonylphenol Ethoxylate Surfactants.A Combined DFT and DPD Study》;Diego Valencia,et al.;《Molecules》;20131231;第18卷(第8期);第9441-9450页 *
《Gemini表面活性剂的性能表征及计算机模拟研究》;朱森;《中国博士学位论文全文数据库 工程科技Ⅰ辑》;20090415(第4期);第B014-32页 *
《Multi-property Fitting and Parameterization of a Coarse Grained Model for Aqueous Surfactants》;Wataru Shinoda,et al.;《Molecular Simulation》;20070131;第1-13页 *
《基于耗散粒子动力学对表面活性剂油水界面性质的研究》;杨善文;《中国优秀硕士学位论文全文数据库 工程科技Ⅰ辑》;20190115(第1期);第B019-270页 *

Also Published As

Publication number Publication date
CN110517733A (en) 2019-11-29

Similar Documents

Publication Publication Date Title
CN110517733B (en) Method for constructing dissipative particle dynamic force field
Martys et al. Velocity Verlet algorithm for dissipative-particle-dynamics-based models of suspensions
Pidaparti et al. Computational simulation of multi-pit corrosion process in materials
Hayati et al. Comparative metrics for computational approaches in non-uniform street-canyon flows
Yao et al. The effects of particle clustering on hindered settling in high-concentration particle suspensions
CN113297777B (en) Multi-scale numerical simulation method and system for acidification reaction flow of carbonate rock oil and gas reservoir
CN112613211B (en) Deformation decomposition method for any triangular unit in planar structure
Oishi et al. Sustainable computational mechanics assisted by deep learning
CN110569604B (en) Dissipative particle dynamics method for simulating reverse osmosis membrane pollution caused by organic matters
CN114638143B (en) Coupling numerical calculation method suitable for simulating water elasticity problem
CN109902354B (en) Interface compression-based simulated multiphase flow interface capturing method
Khoshnaw Dynamic analysis of a predator and prey model with some computational simulations
Chiu et al. Mathematical models and simulations of bacterial growth and chemotaxis in a diffusion gradient chamber
Huang et al. Parallel Performance and Optimization of the Lattice Boltzmann Method Software Palabos Using CUDA
Zermani et al. On a reaction–diffusion system of flocculation type
Tsou Applying computational fluid dynamics to architectural design development
Chaaban et al. A multiscale study of the retention behavior and hydraulic anisotropy in deformable porous media
CN116484509B (en) Complex thin-wall structure optimization design method based on embedded component
Stephanopoulos Dynamics of mixed cultures of microorganisms: Some topological considerations
Guiaş A stochastic approach for simulating spatially inhomogeneous coagulation dynamics in the gelation regime
EL MAANI et al. CFD Analysis and Shape Optimization of NACA0012 Airfoil for Different Mach Numbers
LEDAS et al. COMPUTATIONAL MODELING OF SELF-ORGANIZATION OF BACTERIAL POPULATION CONSISTING OF SUBPOPULATIONS OF ACTIVE AND PASSIVE CELLS
CN113111610B (en) Sub-lattice scale model establishing method
Soualhi et al. The Finite Volume Method Applied to The Patlak-Keller-Segel Chemotaxis Model in a General Mesh
CN118032613A (en) Pile body microscopic scale flow field detection method, device, equipment and storage medium

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
CB03 Change of inventor or designer information
CB03 Change of inventor or designer information

Inventor after: Ma Zhao ring

Inventor after: Gui Shuanglin

Inventor after: Xiong Jihai

Inventor after: Wu Jiujiu

Inventor after: Fu Jia Qi

Inventor after: Yan Bing

Inventor after: Yi Qizhen

Inventor after: Zhang Miaohui

Inventor before: Gui Shuanglin

Inventor before: Ma Zhao ring

Inventor before: Xiong Jihai

Inventor before: Wu Jiujiu

Inventor before: Fu Jia Qi

Inventor before: Yan Bing

Inventor before: Yi Qizhen

Inventor before: Zhang Miaohui

GR01 Patent grant
GR01 Patent grant