CN113515854B - Molecular dynamics method for evaluating charged activated water mist atomization dust-settling performance - Google Patents
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Abstract
The invention discloses a molecular dynamics method for evaluating charged activated water mist atomization dust fall performance, which comprises the steps of constructing different cell models by using a Materials Studio (MS) software AC module, and carrying out geometric optimization, annealing and molecular dynamics relaxation on the constructed cell models by a Forcit module, and relates to the calculation by using script in electric field operation. And acquiring intermolecular interaction energy, the number of head-group water molecules of the surfactant and the diffusion coefficient of the water molecules in the system by adopting a Forcite analysis function. The invention clarifies the charged activated water mist dust-settling performance from the molecular angle, reveals the intermolecular micro-action mechanism of different systems, evaluates different charged activated water mist atomization dust-settling effects from the molecular angle, provides reference for the optimization of an active agent and the acquisition of the optimal charged parameters, and avoids the defects of long period and high cost of the traditional experiment.
Description
Technical Field
The invention belongs to the technical field of dust control, and particularly relates to a molecular dynamics method for evaluating charged activated water mist atomization dust fall performance.
Background
Along with the continuous improvement of the mechanization degree in the coal mining field, the concentration of underground dust of a coal mine tends to rise, the visibility of an underground operation space is reduced, and the accident occurrence probability and the first-line worker sick probability are increased.
At present, the dust is mainly reduced by spraying pure water underground, and the pure water has high surface tension and cohesive force, is not easy to break and has low interaction with coal dust, so that a water mist charging technology and an activated water dust reducing technology become important means. Both suffer from certain deficiencies. The activating agent is added into the pure water to be changed into the activated water, the more the activating agent is, the higher the cost is, and if the degrading efficiency of the activating agent is low, the secondary pollution is caused. For the charged water mist technology, when the water mist catches dust and falls into the ground, static electricity disappears, and the problem of secondary dust raising is caused. Based on the above, a charged activated water mist dust settling technology is provided, and the synergistic effect of different activated water and charged water mist is not clear.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a molecular dynamics method for evaluating the atomization and dust fall performance of charged activated water mist, tests the atomization performance and dust fall effect of the charged activated water mist from the molecular angle, and discloses the atomization mechanism and dust fall mechanism of the charged activated water mist. The interaction energy between the charged activated water and coal molecules can be determined through intermolecular interaction energy, the water retention performance of the charged activated water can be determined through the number of water molecules near a hydrophilic group of a surfactant in the activated water, and the foamability of the charged activated water can be determined through the diffusion coefficient of the water molecules, so that the optimal atomized dust fall parameter of the charged activated water is determined, and the defects of long period and high cost of the traditional experiment are avoided.
The technical scheme adopted by the invention for solving the technical problem is as follows: a molecular dynamics method for evaluating charged activated water mist atomization dust fall performance is constructed, and comprises the following steps:
building molecular structures of coal molecules, water molecules in tap water, different ions and different chemical additives, and performing structural optimization to obtain basic units for building a multi-molecular model;
constructing an amorphous crystal cell model of activated water, coal molecules and a surfactant based on basic units of a multi-molecule model, and setting the shape of the crystal cell to be spherical or square according to needs; performing geometric optimization and dynamic relaxation on the built crystal cell model, selecting NPT (nonlinear programming) in an ensemble, and annealing the NPT; carrying out charge treatment on the activated water to obtain charged activated water;
constructing different charged activated water/coal and surfactant/activated water/surfactant models based on a multi-molecular unit cell model, carrying out geometric optimization on the charged activated water/coal and surfactant/activated water/surfactant models, carrying out kinetic relaxation on the charged activated water/coal models, selecting NVT (noise, vibration and harshness) in an ensemble, and carrying out kinetic relaxation on the surfactant/activated water/surfactant models;
the method comprises the steps of obtaining intermolecular mutual energy of charged activated water/coal models and the number of hydrogen bonds between charged activated water molecules, obtaining the number of water molecules near a head group of a surfactant in the activated water and the diffusion coefficient of the water molecules of the surfactant/activated water/surfactant models, and performing molecular dynamics evaluation on the charged activated water mist atomization dust fall performance through calculation and comparison.
Wherein the coal molecular structure is determined by X-ray photoelectron spectroscopy (XPS), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), or nuclear magnetic resonance carbon spectroscopy (C: (X-ray diffraction)) ( 13 C NMR) is carried out; doml is adopted for optimizing the structure of coal molecule, water and different chemical additives 3 The module is used for selecting Geometry Optimization by a task, wherein a density functional method is GGA, a functional form is PW91, and the precision is set as Fine.
The method comprises the steps of building Amorphous unit cells of activated water, coal molecules and a surfactant by using an Amorphous Cell module in Materials studio software, selecting Construction for a task, setting precision as Fine, setting density according to the built unit cells, setting the number of molecules of different chemical substances in the activated water according to different requirements, selecting Compass II for a force field, selecting Forcefield kind assembled for charges, selecting EWald for an electrostatic non-bond summation method, and selecting EWald for a Van der Waals non-bond summation method.
The method comprises the steps of adopting a Forcite module in Materials studio software to carry out geometric optimization and dynamic relaxation on a built unit cell model, setting the precision to be Ultra-fine, setting the maximum iteration step number of the geometric optimization to be 50000, setting a dynamic relaxation task to be dynamic, setting the ensemble to be NPT, setting a temperature control function to be NHL, setting a pressure control function to be Berendsen, setting the temperature to be 298K, setting the time step to be 1fs, setting the total simulation time to be 1000ps, selecting Compass II for a force field, selecting Forcefield associated for charges, selecting EWALD for an electrostatic non-bond summation method, and selecting EWALD for a Van der Waals non-bond summation method.
In the annealing process, the precision is set to be Ultra-fine, the number of annealing cycle steps is set to be 10, the initial temperature is set to be 298K, the middle cycle temperature is set to be 1098K, and the structure with the minimum energy is selected from the results.
The method comprises the following steps of carrying out electric charge treatment on activated water by adopting script, wherein the electric charge parameters are field intensity, and the magnitude and the direction are given according to actual conditions.
The method comprises the steps of constructing different charged activated water/coal and surfactant/activated water/surfactant models by using a Build Layer tool, selecting a crystal cell with the minimum energy in annealing for construction, selecting a first Layer or a second Layer according to needs, reserving vacuum layers on the upper Layer surface and the lower Layer surface, performing geometric optimization on the charged activated water/coal and surfactant/activated water/surfactant models by using a Forcite module, performing dynamic relaxation on the charged activated water/coal models, performing dynamic relaxation on the surfactant/activated water/surfactant models by using script, endowing the size and the direction of an electric field according to actual conditions, and endowing the ensemble with NVT.
Wherein, the formula for calculating the intermolecular mutual energy is as follows:
E total ＝E Kinetic +E Potential
in the formula, E Kinetic Is intermolecular kinetic energy, E Potential Is intermolecular potential energy;
the formula of the molecular kinetic energy is
In the formula, K B Boltzmann constant, T is temperature;
the molecular potential energy calculation formula is as follows:
E Potential ＝E valence +E crossterm +E non-bond
in the formula E valence Is a valence bond energy, E crossterm Being covalently cross-member energy, E non-bond Is not a bond energy.
Wherein, the calculation formula of the number of water molecules near the hydrophilic group of the surfactant in the activated water is as follows:
wherein g (r) is the probability of water molecule appearing at a distance of r from the head group of the surfactant, N is the number of water molecules in the system, 4 π r 2 dr is the volume of the spherical shell and dr is the spacing
a x b x c is the volume of the model, N head group Is the total number of head groups of the surfactant.
Wherein, the water molecule diffusion coefficient calculation formula is
In the formula r i (0) Position of water molecule when t is 0, r i And (t) is the position of water molecules at the time t.
The invention is different from the prior art, and discloses a molecular dynamics method for evaluating charged activated water mist atomization dust fall performance. And acquiring intermolecular interaction energy, the number of head-group water molecules of the surfactant and the diffusion coefficient of the water molecules in the system by adopting a Forcite analysis function. The invention clarifies the charged activated water mist dust-settling performance from the molecular angle, reveals the micro-action mechanism among different system molecules, evaluates different charged activated water mist atomization dust-settling effects from the molecular angle, provides reference for the optimization of dust suppressant and the acquisition of the optimal charged parameter, and avoids the defects of long period and high cost of the traditional experiment.
Drawings
The invention will be further described with reference to the accompanying drawings and examples, in which:
fig. 1 is a schematic flow chart of a molecular dynamics method for evaluating charged activated water mist atomization dust-settling performance provided by the invention.
FIG. 2 is a schematic diagram of the number of water molecules near head groups of different surfactants in the molecular dynamics method for evaluating the charged activated water mist atomization dust fall performance.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described are only for illustrating the present invention and are not to be construed as limiting the present invention. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, shall fall within the protection scope of the present invention.
Referring to the attached figure 1, the invention provides a molecular dynamics method for evaluating charged activated water mist atomization dust fall performance, which comprises the following steps:
constructing molecular structures of coal molecules, water molecules in tap water, different ions and different chemical additives, and performing structural optimization to obtain basic units for constructing a multi-molecular model;
constructing an amorphous crystal cell model of activated water, coal molecules and a surfactant based on basic units of a multi-molecule model, and setting the shape of the crystal cell to be spherical or square according to needs; performing geometric optimization and dynamic relaxation on the built crystal cell model, selecting NPT (nonlinear programming) in an ensemble, and annealing the NPT; carrying out charge treatment on the activated water to obtain charged activated water;
constructing different charged activated water/coal and surfactant/activated water/surfactant models based on a multi-molecular unit cell model, carrying out geometric optimization on the charged activated water/coal and surfactant/activated water/surfactant models, carrying out kinetic relaxation on the charged activated water/coal models, selecting NVT (noise, vibration and harshness) in an ensemble, and carrying out kinetic relaxation on the surfactant/activated water/surfactant models;
the method comprises the steps of obtaining intermolecular mutual energy of charged activated water/coal models and the number of hydrogen bonds between charged activated water molecules, obtaining the number of water molecules near a head group of a surfactant in the activated water and the diffusion coefficient of the water molecules of the surfactant/activated water/surfactant models, and performing molecular dynamics evaluation on the charged activated water mist atomization dust fall performance through calculation and comparison.
Wherein the coal molecular structure is determined by X-ray photoelectron spectroscopy (XPS), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD) or nuclear magnetic resonance carbon spectroscopy (C 13 C NMR) is carried out; doml is adopted for optimizing the structure of coal molecules, water and different chemical additives 3 And the module is used for selecting Geometry Optimization by a task, wherein the density functional method is GGA, the functional form is PW91, and the precision is set as Fine.
The method comprises the steps of building Amorphous unit cells of activated water, coal molecules and a surfactant by using an Amorphous Cell module in Materials studio software, selecting Construction for a task, setting precision as Fine, setting density according to the built unit cells, setting the number of molecules of different chemical substances in the activated water according to different requirements, selecting Compass II for a force field, selecting Forcefield kind assembled for charges, selecting EWald for an electrostatic non-bond summation method, and selecting EWald for a Van der Waals non-bond summation method.
The method comprises the steps of adopting a Forcite module in Materials studio software to carry out geometric optimization and dynamic relaxation on a built unit cell model, setting the precision to be Ultra-fine, setting the maximum iteration step number of the geometric optimization to be 50000, setting a dynamic relaxation task to be dynamic, setting the ensemble to be NPT, setting a temperature control function to be NHL, setting a pressure control function to be Berendsen, setting the temperature to be 298K, setting the time step to be 1fs, setting the total simulation time to be 1000ps, selecting Compass II for a force field, selecting Forcefield associated for charges, selecting EWALD for an electrostatic non-bond summation method, and selecting EWALD for a Van der Waals non-bond summation method.
In the annealing process, the precision is set to be Ultra-fine, the number of annealing cycle steps is set to be 10, the initial temperature is set to be 298K, the intermediate cycle temperature is set to be 1098K, and the structure with the minimum energy is selected from the results.
The method comprises the following steps of carrying out electric charge treatment on activated water by adopting script, wherein the electric charge parameters are field intensity, and the magnitude and the direction are given according to actual conditions.
The method comprises the steps of constructing different charged activated water/coal and surfactant/activated water/surfactant models by using a Build Layer tool, selecting a crystal cell with the minimum energy in annealing for construction, selecting a first Layer or a second Layer according to needs, reserving vacuum layers on the upper Layer surface and the lower Layer surface, performing geometric optimization on the charged activated water/coal and surfactant/activated water/surfactant models by using a Forcite module, performing dynamic relaxation on the charged activated water/coal models, performing dynamic relaxation on the surfactant/activated water/surfactant models by using script, endowing the size and the direction of an electric field according to actual conditions, and endowing the ensemble with NVT.
Wherein, the formula for calculating the intermolecular mutual energy is as follows:
E total ＝E Kinetic +E Potential
in the formula, E Kinetic Is intermolecular kinetic energy, E Potential Is intermolecular potential energy;
the formula of the molecular kinetic energy is
In the formula, K B Boltzmann constant, T is temperature;
the molecular potential energy calculation formula is as follows:
E Potential ＝E valence +E crossterm +E non-bond
in the formula E valence Is a valence bond energy, E crossterm Being covalently cross-linked, E non-bond Is a non-bonding energy.
Wherein, the calculation formula of the number of water molecules near the hydrophilic group of the surfactant in the activated water is as follows:
wherein g (r) is the probability of water molecule appearing at a distance of r from the head group of the surfactant, N is the number of water molecules in the system, 4 π r 2 dr is the volume of the spherical shell and dr is the spacing
a x b x c is the volume of the model, N head group Is the total number of head groups of the surfactant.
Wherein, the water molecule diffusion coefficient calculation formula is
In the formula r i (0) Position of water molecule when t is 0, r i And (t) is the position of water molecules at the time t.
In this example, the coal type is the basic unit of bituminous coal, and the activating water is pure water with sodium dodecyl sulfate added. And sequentially drawing a basic unit structure of the bituminous coal, a molecular structure of lauryl sodium sulfate and a molecular structure of water molecules and different ions in tap water by using a Sketch tool in MS. Using Doml 3 The module optimizes the Optimization, the task selects Geometry Optimization, the density functional method is GGA, the functional form is PW91, and the precision is set as Fine.
And constructing a bituminous coal spherical amorphous crystal cell, an activated water spherical amorphous crystal cell, a water molecule square amorphous crystal cell and a lauryl sodium sulfate square amorphous crystal cell by adopting an AC module. The parameters are set as follows: selecting Construction for a task, setting precision as Fine, setting density according to built unit cells, setting the number of molecules of different chemical substances in activated water according to different requirements, selecting Compass II for a force field, selecting Forcefield assembled for a charge, selecting EWALD for an electrostatic non-bond summation method, and selecting EWALD for a Van der Waals non-bond summation method.
And (3) adopting a Forcite module to carry out structural optimization on the bituminous coal spherical amorphous unit cell, the activated water spherical amorphous unit cell, the pure water molecule square amorphous unit cell and the lauryl sodium sulfate square amorphous unit cell. Setting related parameters: the precision is set to Ultra-fine, the maximum iteration step number of the geometric optimization is set to 50000, and if the unit cell does not reach the optimal structure, further optimization is needed. Then, performing dynamic relaxation on the optimal structure, and setting related parameters: the tasks are set to Dynamics, ensemble NPT, temperature control function is set to NHL, pressure control function is set to Berendsen, temperature is set to 298K, time step is set to 1fs, and total simulation time is set to 1000 ps. The settings for the force field parameters, charge distribution and non-key summation methods are the same as described above. And judging whether the cell model can represent a real structure according to different cell densities after the dynamic relaxation.
Annealing the kinetically relaxed bituminous coal spherical amorphous unit cells, activated water spherical amorphous unit cells, pure water molecule square amorphous unit cells and sodium dodecyl sulfate square amorphous unit cells by using an annealing tool. Setting related parameters: the precision was set to Ultra-fine, the number of annealing cycle steps was set to 10, the initial temperature was set to 298K, the mid-cycle temperature was set to 1098K, and the force field parameters, charge distribution mode and non-bond summation method settings were the same as described above. The energy-minimum unit cell is selected from the annealing result.
Carrying out charge treatment on the activated water by adopting script, wherein the charge parameter is field intensity, and the field intensity is
The field strength direction is along the positive x-axis.
A Build Layer tool is adopted to construct a charged activated water/bituminous coal model and a sodium dodecyl sulfate/water/sodium dodecyl sulfate model, and vacuum layers are required to be left above and below the two models. The method is geometrically optimized by adopting a Forcite module, and the parameter setting is the same as that of the Forcite module. And (3) performing dynamic relaxation on the charge activated water/bituminous coal model, wherein the ensemble is NVT, and other parameter settings are the same as those described above. Performing dynamic relaxation on sodium dodecyl sulfate/water/sodium dodecyl sulfate model by adopting script, and setting the electric field size to be
And (3) analyzing the interaction energy of the dynamically relaxed charged activated water/bituminous coal model by adopting a script function, and judging the intermolecular interaction strength according to the size of the interaction energy. The mutual energy is negative, which means that the intermolecular interaction proceeds spontaneously, and the larger the absolute value is, the stronger the intermolecular interaction is. And analyzing the system after the balance is achieved, selecting 190-200 frames, and determining the strength of the action of the charged activated water molecules and the bituminous coal molecules according to the result, wherein the value is-2.51 multiplied by 106 kcal/mol.
The Forcite Analysis software is adopted to obtain the number of water molecules near the head group of sodium dodecyl sulfate in the charged activated water/bituminous coal model, and the larger the number of the water molecules, the stronger the water attraction capacity of the activated water is, so that the larger the number of the water molecules on the surface of the bituminous coal is, the better the wetting effect on the bituminous coal is, and the better the dust fall effect is. Analyzing the system after the balance is achieved, selecting 190-200 frames, setting the head group of the sodium dodecyl sulfate as a segment, setting the water molecules as a segment, and setting the truncation radius as
At an interval of
Calculating the formula (4) by using the obtained radial distribution function g (r), thereby obtaining the number of water molecules near the sodium dodecyl sulfate head group in the charge activated water/bituminous coal model, and obtaining the water molecules in the charge activated water/bituminous coal model2, respectively.
The number of hydrogen bonds of water molecules in the charged activated water is obtained by a script analysis tool, and the fewer the hydrogen bonds among the water molecules are, the lower the cohesion among the water molecules is, the better the atomization effect of the charged activated water is, and the number of the hydrogen bonds among the charged activated water mist is 708.
The diffusion coefficient of water molecules in a surfactant/activated water/surfactant model within 500ps is obtained by adopting Forcite Analysis software. The larger the diffusion coefficient of the water molecules is, the larger the liquidity of the water molecules is, the more easily broken the foam is, the better the atomization effect is and the better the dust settling effect is. Since the spray dustfall technique is superior in the foaming property of the activated water, the dustfall efficiency is low, and its value is 6.855.
While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (2)
1. A molecular dynamics method for evaluating charged activated water mist atomization dust fall performance is characterized by comprising the following steps:
building molecular structures of coal molecules, water molecules in tap water, different ions and different chemical additives, and performing structural optimization to obtain basic units for building a multi-molecular model;
constructing an amorphous crystal cell model of activated water, coal molecules and a surfactant based on basic units of a multi-molecule model, and setting the shape of the crystal cell to be spherical or square according to needs; performing geometric optimization and dynamic relaxation on the built crystal cell model, selecting NPT (nonlinear programming) in an ensemble, and annealing the NPT; carrying out charge treatment on the activated water to obtain charged activated water;
constructing different charged activated water/coal and surfactant/activated water/surfactant models based on a multi-molecular unit cell model, carrying out geometric optimization on the charged activated water/coal and surfactant/activated water/surfactant models, carrying out kinetic relaxation on the charged activated water/coal models, selecting NVT (noise, vibration and harshness) in an ensemble, and carrying out kinetic relaxation on the surfactant/activated water/surfactant models;
acquiring the intermolecular mutual energy of the charged activated water/coal model and the number of hydrogen bonds between charged activated water molecules, acquiring the number of water molecules near the head group of the surfactant in the activated water and the diffusion coefficient of the water molecules of the surfactant/activated water/surfactant model, and performing molecular dynamics evaluation on the charged activated water mist atomization dust fall performance through calculation and comparison;
establishing an Amorphous crystal Cell of activated water, coal molecules and a surfactant by adopting an Amorphous Cell module in Materials studio software, selecting Construction for a task, setting the precision as Fine, setting the density according to the established crystal Cell, setting the number of molecules of different chemical substances in the activated water according to different requirements, selecting Compass II for a force field, selecting Forcefield associated, selecting EWALD for an electrostatic non-bond summation method, and selecting EWALD for a Van der Waals non-bond summation method;
performing geometric optimization and dynamic relaxation on the built unit cell model by adopting a Forcite module in Materials studio software, setting the precision to be Ultra-fine, setting the maximum iteration step number of the geometric optimization to be 50000, setting a dynamic relaxation task to be Dynamics, setting the ensemble to be NPT, setting a temperature control function to be NHL, setting a pressure control function to be Berendsen, setting the temperature to be 298K, setting the time step to be 1fs, setting the total simulation time to be 1000ps, selecting Compass II for a force field, selecting Forcefield aligned for charges, selecting EWALD for an electrostatic nonbonding summation method, and selecting EWALD for a Van der Waals nonbonding summation method;
in the annealing process, the precision is set as Ultra-fine, the number of annealing cycle steps is set as 10, the initial temperature is set as 298K, the intermediate cycle temperature is set as 1098K, and the structure with the minimum energy is selected from the results;
carrying out charge treatment on the activated water by adopting script, wherein charge parameters are field intensity, and the magnitude and the direction are given according to actual conditions;
building different charged activated water/coal and surfactant/activated water/surfactant models by using a Build Layer tool, selecting a crystal cell with the minimum energy in annealing for building, selecting a first Layer or a second Layer as required, reserving vacuum layers on the upper Layer and the lower Layer, performing geometric optimization on the charged activated water/coal and surfactant/activated water/surfactant models by using a Forcite module, performing dynamic relaxation on the charged activated water/coal models, performing dynamic relaxation on the surfactant/activated water/surfactant models by using script, endowing the size and direction of an electric field according to actual conditions, and integrating the model into NVT;
the formula for calculating the intermolecular mutual energy is as follows:
E total ＝E Kinetic +E Potential
in the formula, E Kinetic Is kinetic energy of molecules, E Potential Is molecular potential energy;
the formula of the molecular kinetic energy is
In the formula, K B Boltzmann constant, T is temperature;
the molecular potential energy calculation formula is as follows:
E Potential ＝E valence +E crossterm +E non-bond
in the formula E valence Is valence bond energy, E crossterm Being covalently cross-linked, E non-bond Is a non-bonding energy;
the calculation formula of the number of water molecules near the hydrophilic group of the surfactant in the activated water is as follows:
wherein g (r) is the probability of water molecule appearing at a distance of r from the head group of the surfactant, N is the number of water molecules in the system, 4 π r 2 dr is the volume of the spherical shell, dr is the pitch, a × b × c is the volume of the model, N headgroup Is the total number of head groups of the surfactant;
the water molecule diffusion coefficient is calculated by the formula
In the formula r i (0) Position of water molecule when t is 0, r i And (t) is the position of water molecules at the time t.
2. The method of claim 1, wherein the molecular dynamics of the charged activated water mist atomized dust fall evaluation is characterized in that the coal molecular structure is determined by X-ray photoelectron spectroscopy (XPS), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD) or Nuclear Magnetic Resonance (NMR) carbon spectroscopy 13 Obtaining a CNMR; doml is adopted for optimizing the structure of coal molecules, water molecules in tap water, different ions and different chemical additives 3 The module is used for selecting Geometry Optimization by a task, wherein a density functional method is GGA, a functional form is PW91, and the precision is set as Fine.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105834007A (en) * | 2016-05-28 | 2016-08-10 | 太原理工大学 | Evaluation method for collecting performance of coal flotation collecting agent |
| CN112164425A (en) * | 2020-09-27 | 2021-01-01 | 齐鲁工业大学 | Simulation method of silicon dioxide coated calcium fluoride based on Materials Studio |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11455439B2 (en) * | 2018-11-28 | 2022-09-27 | Robert Bosch Gmbh | Neural network force field computational algorithms for molecular dynamics computer simulations |
| CN110556168B (en) * | 2019-09-11 | 2022-07-05 | 江西省科学院能源研究所 | Simulation method for analyzing diffusion property of water-soluble monomer in gel film |
| CN111243683B (en) * | 2020-01-13 | 2023-04-07 | 重庆大学 | Method for guiding cellulose molecule design and dielectric property evaluation |
| CN111192628B (en) * | 2020-02-27 | 2023-03-24 | 西安理工大学 | Oxygen diffusion coefficient calculation method of polydimethylsiloxane |
-
2021
- 2021-06-10 CN CN202110645534.XA patent/CN113515854B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105834007A (en) * | 2016-05-28 | 2016-08-10 | 太原理工大学 | Evaluation method for collecting performance of coal flotation collecting agent |
| CN112164425A (en) * | 2020-09-27 | 2021-01-01 | 齐鲁工业大学 | Simulation method of silicon dioxide coated calcium fluoride based on Materials Studio |
Non-Patent Citations (6)
| Title |
|---|
| Experimental Study on Characteristics of Methane-Coal-Dust Mixture Explosion and Its Mitigation by Ultra-Fine Water Mist;Hongli XU 等;《Journal of Engineering for Gas Turbines and Power》;20120630;第134卷(第6期);第1-8页 * |
| 利用浮动电荷力场对N-甲基乙酰胺水溶液的分子动力学模拟;张强 等;《化学学报》;20061230;第64卷(第24期);第2425-2430页 * |
| 新型高分子抑尘剂的性能实验研究;葛少成 等;《中国安全生产科学技术》;20161030;第12卷(第10期);第56-61页 * |
| 水雾荷电性能及其降尘效果实验研究;孙丽英;《中国优秀博硕士学位论文全文数据库(硕士)工程科技Ⅰ辑》;20200715(第07期);第B021-160页 * |
| 粒径、水分对煤中甲烷的吸附-扩散实验研究;刘炎杰 等;《煤》;20150415;第24卷(第4期);第12-18页 * |
| 采用荷电活化水预荷电除尘与机理分析;吴宝元 等;《黄金学报》;19960215;第15卷(第1期);第59-61页 * |
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