CN115536269A - Method for determining glass component and method for producing glass - Google Patents
Method for determining glass component and method for producing glass Download PDFInfo
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- CN115536269A CN115536269A CN202211318600.3A CN202211318600A CN115536269A CN 115536269 A CN115536269 A CN 115536269A CN 202211318600 A CN202211318600 A CN 202211318600A CN 115536269 A CN115536269 A CN 115536269A
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- 239000011521 glass Substances 0.000 title claims abstract description 112
- 238000000034 method Methods 0.000 title claims abstract description 42
- 238000004519 manufacturing process Methods 0.000 title description 12
- 238000012360 testing method Methods 0.000 claims abstract description 68
- 238000001816 cooling Methods 0.000 claims abstract description 42
- 238000004088 simulation Methods 0.000 claims abstract description 34
- 239000000463 material Substances 0.000 claims abstract description 15
- 238000004364 calculation method Methods 0.000 claims abstract description 11
- 238000000329 molecular dynamics simulation Methods 0.000 claims abstract description 8
- 239000000203 mixture Substances 0.000 claims description 26
- 238000005457 optimization Methods 0.000 claims description 18
- 229910018072 Al 2 O 3 Inorganic materials 0.000 claims description 15
- 229910004298 SiO 2 Inorganic materials 0.000 claims description 13
- VYPSYNLAJGMNEJ-UHFFFAOYSA-N silicon dioxide Inorganic materials O=[Si]=O VYPSYNLAJGMNEJ-UHFFFAOYSA-N 0.000 claims description 4
- 238000004510 Lennard-Jones potential Methods 0.000 claims description 3
- 241000341910 Vesta Species 0.000 claims description 3
- 238000002939 conjugate gradient method Methods 0.000 claims description 3
- 238000011478 gradient descent method Methods 0.000 claims description 3
- 230000000737 periodic effect Effects 0.000 claims description 3
- 235000013550 pizza Nutrition 0.000 claims description 3
- 238000002360 preparation method Methods 0.000 claims description 3
- 239000005361 soda-lime glass Substances 0.000 claims description 3
- 238000002945 steepest descent method Methods 0.000 claims description 3
- 230000008569 process Effects 0.000 abstract description 4
- 239000002699 waste material Substances 0.000 abstract description 4
- 239000005329 float glass Substances 0.000 description 12
- 239000000126 substance Substances 0.000 description 4
- 230000003247 decreasing effect Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 238000002834 transmittance Methods 0.000 description 2
- ATJFFYVFTNAWJD-UHFFFAOYSA-N Tin Chemical compound [Sn] ATJFFYVFTNAWJD-UHFFFAOYSA-N 0.000 description 1
- 238000005520 cutting process Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000012938 design process Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000010413 gardening Methods 0.000 description 1
- 239000007789 gas Substances 0.000 description 1
- 239000001257 hydrogen Substances 0.000 description 1
- 229910052739 hydrogen Inorganic materials 0.000 description 1
- 238000013101 initial test Methods 0.000 description 1
- 238000002844 melting Methods 0.000 description 1
- 230000008018 melting Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000001681 protective effect Effects 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000007493 shaping process Methods 0.000 description 1
- 238000013519 translation Methods 0.000 description 1
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- C—CHEMISTRY; METALLURGY
- C03—GLASS; MINERAL OR SLAG WOOL
- C03C—CHEMICAL COMPOSITION OF GLASSES, GLAZES OR VITREOUS ENAMELS; SURFACE TREATMENT OF GLASS; SURFACE TREATMENT OF FIBRES OR FILAMENTS MADE FROM GLASS, MINERALS OR SLAGS; JOINING GLASS TO GLASS OR OTHER MATERIALS
- C03C3/00—Glass compositions
- C03C3/04—Glass compositions containing silica
- C03C3/076—Glass compositions containing silica with 40% to 90% silica, by weight
- C03C3/083—Glass compositions containing silica with 40% to 90% silica, by weight containing aluminium oxide or an iron compound
- C03C3/085—Glass compositions containing silica with 40% to 90% silica, by weight containing aluminium oxide or an iron compound containing an oxide of a divalent metal
- C03C3/087—Glass compositions containing silica with 40% to 90% silica, by weight containing aluminium oxide or an iron compound containing an oxide of a divalent metal containing calcium oxide, e.g. common sheet or container glass
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
- G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
- G16C20/30—Prediction of properties of chemical compounds, compositions or mixtures
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
- G16C60/00—Computational materials science, i.e. ICT specially adapted for investigating the physical or chemical properties of materials or phenomena associated with their design, synthesis, processing, characterisation or utilisation
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Abstract
The invention relates to a method for determining glass components and a method for preparing glass. The method for determining the glass components mainly comprises the steps of establishing a box model of a test component, optimizing the box model, carrying out cooling simulation on the optimized box model based on molecular dynamics calculation, collecting structural information in the box model, calculating the current performance of glass corresponding to the test component according to the structural information, and comparing the current performance parameters with target performance parameters. In the determination method, test glass does not need to be manufactured, the material waste in the component determination process can be effectively reduced, and a new thought is provided for the determination of the glass components.
Description
Technical Field
The invention relates to the technical field of glass research, in particular to a method for determining glass components and a method for preparing glass.
Background
With the continuous and deep research on glass, the types and properties of glass are greatly enriched. Researchers can design corresponding glass according to the actual use requirements of the glass. In the design process of glass, the glass composition is one of the important factors determining the glass properties. In the process of determining the glass components, different glass components are designed in a traditional mode, then the glass components are made into test glass, then the performance of the test glass is tested, then whether the performance of the glass can meet the requirements or not is evaluated, and then the components of the glass are determined according to the performance evaluation result of the glass. The method has better intuition and better guiding significance for determining the glass components. However, this method requires more test glass to be prepared for performance testing, and thus consumes more test time and causes more material waste.
Disclosure of Invention
Based on this, there is a need for a method of determining a glass component and a method of manufacturing glass that can reduce material waste.
In order to solve the technical problems, the technical scheme of the application is as follows:
a method for determining a glass composition, comprising the steps of:
step S101: establishing a box model of atoms of the test component;
step S102: carrying out structural optimization on the box model;
step S103: performing cooling simulation on the optimized box model based on molecular dynamics calculation, and acquiring structural information in the box model in the cooling simulation;
step S104: calculating the current performance parameters of the glass corresponding to the test components according to the structural information;
step S105: and comparing the current performance parameter with a target performance parameter, taking the test component as a target component when the current performance parameter meets the requirement of the target performance parameter, otherwise, adjusting the test component, repeating the steps S101-S104 by using the adjusted test component until the current performance parameter meets the requirement of the target performance parameter, and taking the adjusted test component as the target component.
In one embodiment, the glass to which the test component corresponds is a soda-lime-silica glass.
In one embodiment, the test component comprises SiO 2 、Al 2 O 3 、Na 2 O, mgO, and CaO.
In one embodiment, the test component comprises 68-78% SiO by mass 2 0.1 to 3 percent of Al 2 O 3 11 to 18 percent of Na 2 O, 0 to 1 percent of K 2 O, 1.5 to 6.5 percent of MgO, 6.5 to 12 percent of CaO and less than or equal to 0.01 percent of Fe 2 O 3 。
In one embodiment, the box model is built by one or more of Materials Studio, matlab, and LAMMPS.
In one embodiment, the boundary conditions used to create the box model are periodic boundary conditions and/or fixed boundary conditions.
In one embodiment, the force field type for establishing the box model is CVFF and/or PVFF.
In one embodiment, the box model is in the shape of a cube.
In one embodiment, the single side of the box model is 47.2 angstroms to 51.4 angstroms in length.
In one embodiment, the density of atoms in the box model is 2.30g/cm 3 ～2.59g/cm 3 。
In one embodiment, the structural optimization is performed by one or more of Materials Studio, matlab, and LAMMPS.
In one embodiment, the structural optimization is geometric optimization.
In one embodiment, the structural optimization utilizes a gradient descent method, a conjugate gradient method, or a steepest descent method for energy minimization.
In one embodiment, the cooling simulation employs an ensemble that is at least one of an NVT ensemble, an NPT ensemble, and an NVE ensemble.
In one embodiment, the cooling speed of the cooling simulation is 1K/ps-20K/ps.
In one embodiment, the initial temperature of the cooling simulation is 4000K to 5000K, and the temperature after the cooling simulation is 250K to 350K.
In one embodiment, the step length of the cooling time of the cooling simulation is 1 fs/step to 5 fs/step.
In one embodiment, in the cooling simulation, when the temperature is reduced to the target temperature, the relaxation of 20ps to 50ps is performed at the target temperature.
In one embodiment, the frequency of collecting the structural information in the box model is 100 steps/time to 1000 steps/time.
In one embodiment, the acquisition range is confirmed by a potential function including one or more of a Lennard-Jones potential function, a Morse potential function, and a Born-Mayer potential function when acquiring the structural information within the box model.
In one embodiment, the current performance parameters of the glass corresponding to the test components are calculated according to the structural information by using one or more of VMD, OVITO, VESTA, and PIZZA.
A method of making glass comprising the steps of:
determining a target component of the glass using the determination method described in any of the above examples;
the glass is prepared with the target components.
The method for determining the glass components mainly comprises the steps of establishing a box model of test components, optimizing the box model, performing cooling simulation on the optimized box model based on molecular dynamics calculation, acquiring structural information in the box model, calculating the current performance of glass corresponding to the test components according to the structural information, comparing the current performance parameters with target performance parameters, taking the test components as the target components when the current performance parameters meet the requirements of the target performance parameters, otherwise, adjusting the test components, repeatedly establishing the box model-structural optimization-cooling simulation by the adjusted test components, acquiring the structural information-calculating the current performance parameters until the current performance parameters meet the requirements of the target performance parameters, and taking the adjusted test components as the target components. In the determination method, molecular dynamics calculation is introduced, the relation between the glass performance and the glass components can be obtained on a molecular level, the adjustment of the glass components is guided according to the performance parameters obtained by calculation, and the glass components meeting the requirements of target performance parameters are further obtained.
Drawings
Fig. 1 is a schematic diagram of a cassette model in embodiment 1 of the present application.
FIG. 2 is a diagram showing the atomic and chemical information in the box model in example 1 of the present application.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein.
In the present invention, unless otherwise explicitly stated or limited, the terms "mounted," "connected," "fixed," and the like are to be construed broadly, e.g., as being permanently connected, detachably connected, or integral; can be mechanically or electrically connected; they may be directly connected or indirectly connected through intervening media, or they may be connected internally or in any other suitable relationship, unless expressly stated otherwise. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
One embodiment of the present application provides a method for determining a glass composition. The method for determining the glass component comprises the following steps:
step S101: establishing a box model of atoms of the test components;
step S102: carrying out structural optimization on the box model;
step S103: performing cooling simulation on the optimized box model based on molecular dynamics calculation, and acquiring structural information in the box model in the cooling simulation;
step S104: calculating the current performance parameters of the glass corresponding to the test components according to the structural information;
step S105: and comparing the current performance parameter with the target performance parameter, taking the test component as the target component when the current performance parameter meets the requirement of the target performance parameter, otherwise, adjusting the test component, repeating the steps S101-S104 by using the adjusted test component until the current performance parameter meets the requirement of the target performance parameter, and taking the adjusted test component as the target component.
In this embodiment, the method for determining the glass component mainly includes building a box model of a test component, optimizing the box model, performing cooling simulation on the optimized box model based on molecular dynamics calculation, collecting structural information in the box model, calculating current performance of glass corresponding to the test component according to the structural information, comparing the current performance parameter with a target performance parameter, taking the test component as the target component when the current performance parameter meets the requirement of the target performance parameter, otherwise, adjusting the test component, repeating building box model-structure optimization-cooling simulation with the adjusted test component, collecting structural information-calculating the current performance parameter until the current performance parameter meets the requirement of the target performance parameter, and taking the adjusted test component as the target component. In the determination method, molecular dynamics calculation is introduced, the relation between the glass performance and the glass components can be obtained on a molecular level, the adjustment of the glass components is guided according to the performance parameters obtained by calculation, and the glass components meeting the requirements of target performance parameters are further obtained. In addition, the method for determining the glass components in the embodiment is time-saving, labor-saving, cost-saving and has higher efficiency compared with the traditional method for manufacturing test glass.
It is to be understood that, in the above-described method for determining a glass component, when the current performance parameter does not satisfy the requirement of the target performance parameter in step S105, the manner of adjusting the test components may be adjusting the ratio of each component in the test components, such as adjusting the mass percentage of each component in the test components to the test components. When adjusting the test components, the adjustment directions of the proportions of the components in the test components may be the same or different. For example, when the test components are adjusted, the ratios of the components in the test components may be adjusted in the increasing direction, in the decreasing direction, in the increasing direction, or in the decreasing direction.
In a specific example, the above-described method for determining the glass composition is applied to determination of the composition of ultra-white glass. The ultra-white glass generally refers to glass with visible light transmittance higher than 91%, has glittering and translucent characteristics, and is widely applied to the fields of solar photovoltaic, cars, buildings, gardening, furniture and the like. With the increasing demand of consumers, the demand and the application range of ultra-white glass are increasing. The method for determining the components of the glass can quickly determine the components of the ultra-white glass, so as to guide the production of the ultra-white glass, improve the production efficiency of the ultra-white glass, reduce the waste of materials in the preparation process of the ultra-white glass and reduce the material cost of the ultra-white glass.
Further, the above method for determining the glass composition is suitable for determining the composition of ultra-white float glass. Float glass has many advantages, such as high transparency, smooth hand, good flatness, easy cutting, etc. However, float glass, as a special glass, also has some differences in the manufacturing process, and the forming process is usually carried out in a tin bath with a protective gas. This indicates that float glass has some specificity in the manufacturing process, where it may take more time and material to determine the composition of the glass in the manner that it is conventionally tested to make test glass and to test the properties of the glass. The method for determining the components of the ultra-white float glass can be used for determining the components of the ultra-white float glass without preparing test glass for testing, can be used for quickly determining the components of the ultra-white float glass, guiding the production of the ultra-white float glass, reducing the material cost of the ultra-white float glass and improving the processing efficiency of the ultra-white float glass.
In a specific example, the structural information in the cassette model includes information such as chemical bond information, basic structural unit information, connection form between structural units, and distance information.
In one particular example, the glass to which the test components correspond is soda-lime-silica glass.
In one particular example, the test component comprises SiO 2 、Al 2 O 3 、Na 2 O, mgO, and CaO. Alternatively, in the test component, siO 2 、Al 2 O 3 、Na 2 The sum of the mass percentages of O, mgO and CaO is greater than or equal to 99%. Optionally, the test component further comprises K 2 O and/or Fe 2 O 3 . Alternatively, in the test components, C1= O/Si is 1.1 to 4.6, and C2= SiO 2 The ratio of/RO is 3.5-10.5, and C3= R 2 O/RO is 0.7-2.2, RO is MgO, caO, R 2 O is Na 2 O、K 2 O, C1, C2 and C3 represent mass ratios.
In one particular example, the target component includes SiO 2 、Al 2 O 3 、Na 2 O, mgO, and CaO. Optionally, in the target component, siO 2 、Al 2 O 3 、Na 2 The sum of the mass percentages of O, mgO and CaO is greater than or equal to 99%. Optionally, the target component further comprises K 2 O and/or Fe 2 O 3 . Optionally, in the target component, C1= O/Si is 1.1 to 4.6, and C2= SiO 2 The ratio of/RO is 3.5-10.5, and C3= R 2 O/RO is 0.7-2.2, RO is MgO, caO, R 2 O is Na 2 O、K 2 O, C1, C2 and C3 represent mass ratios.
Optionally, the test component comprises 68-78% SiO by mass 2 0.1 to 3 percent of Al 2 O 3 11 to 18 percent of Na 2 O, 0 to 1% of K 2 O, 1.5 to 6.5 percent of MgO, and 6.5 to 1 percent of2% CaO and less than or equal to 0.01% Fe 2 O 3 。
In one particular example, the target composition includes 68% to 78% SiO 2 0.1 to 3 percent of Al 2 O 3 11 to 18 percent of Na 2 O, 0 to 1% of K 2 O, 1.5 to 6.5 percent of MgO, 6.5 to 12 percent of CaO and less than or equal to 0.01 percent of Fe 2 O 3 。
In yet another embodiment, the present disclosure provides a glass comprising, in mass percent, 68% to 78% SiO 2 0.1 to 3 percent of Al 2 O 3 11 to 18 percent of Na 2 O, 0 to 1% of K 2 O, 1.5 to 6.5 percent of MgO, 6.5 to 12 percent of CaO and less than or equal to 0.01 percent of Fe 2 O 3 . Alternatively, the composition of the glass is determined by the above-described determination method of the glass composition. Further, in the glass, siO 2 、Al 2 O 3 、Na 2 The sum of the mass percentages of O, mgO and CaO is greater than or equal to 99%. Optionally, the test component further comprises K 2 O and/or Fe 2 O 3 . Alternatively, in the glass, C1= O/Si is 1.1 to 4.6, and C2= SiO 2 The ratio of/RO is 3.5-10.5, and C3= R 2 O/RO is 0.7-2.2, RO is MgO, caO, R 2 O is Na 2 O、K 2 O, C1, C2 and C3 represent mass ratios. Optionally, the glass is ultra-white glass. Optionally, the glass is ultra-white float glass.
As can be appreciated, siO 2 The mass percentage of (b) may be, but is not limited to, 68%, 69%, 70%, 71%, 72%, 73%, 74%, 75%, 76%, 77%, 78%, etc. Al (Al) 2 O 3 The mass percentage of (b) may be, but is not limited to, 0.1%, 0.2%, 0.5%, 0.8%, 0.9%, 1%, 1.2%, 1.4%, 1.5%, 1.8%, 2%, 2.2%, 2.5%, 2.8%, 3%, etc. Na (Na) 2 The mass percentage of O may be, but is not limited to, 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18%, etc. K 2 The mass percentage of O may be, but is not limited to, 0%, 0.1%, 0.2%, 0.3%, 0.4%, 0.5%,0.6%, 0.7%, 0.8%, 0.9%, 1%, etc. The mass percentage of MgO may be, but is not limited to, 1.5%, 1.8%, 2%, 2.5%, 2.8%, 3%, 3.5%, 3.8%, 4%, 4.5%, 4.8%, 5%, 5.5%, 5.8%, 6%, 6.5%, etc. The mass percentage of CaO may be, but is not limited to, 6.5%, 7%, 7.5%, 8%, 8.2%, 8.5%, 9%, 9.5%, 10%, 10.5%, 11%, 11.5%, 12%, etc. Fe 2 O 3 The mass percentage of (b) may be, but is not limited to, 0.01% or less, 0.005% or less, 0.001% or less, 0.0005% or less, 0.0001% or less, etc.
As some specific examples of the determination method of the glass composition, a box model is established by one or more of Materials Studio, matlab, and LAMMPS. The boundary conditions used to build the box model are periodic boundary conditions and/or fixed boundary conditions. The force field type of the box model is CVFF and/or PVFF. The shape of the box model is a cube shape, for example, the shape of the box model can be a cuboid, a cube, or the like. Alternatively, the length of the single side of the cassette model is 47.2 to 51.4 angstroms (1 angstrom =0.1 nm), and the length of the single side of the cassette model can be determined to be 47.2 to 51.4 angstroms according to the number of atoms in the cassette model. For example, when the number of atoms in the cassette model is 8000 to 10000, the length of one side of the cassette model is 47.2 to 51.4. Optionally, the box model is a cube having sides of 47.2-51.4 angstroms. Optionally, the density of atoms in the box model is 2.30g/cm 3 ～2.59g/cm 3 . For example, the density of atoms in the box model may be, but is not limited to, 2.30g/cm 3 、2.35g/cm 3 、2.40g/cm 3 、2.45g/cm 3 、2.46g/cm 3 、2.48g/cm 3 、2.50g/cm 3 、2.52g/cm 3 、2.55g/cm 3 、2.58g/cm 3 、2.59g/cm 3 And so on.
In one particular example, the structural optimization is performed by one or more of Materials Studio, matlab, and LAMMPS. Optionally, the structural optimization is geometric optimization. Further optionally, the structural optimization utilizes a gradient descent method, a conjugate gradient method, or a steepest descent method for energy minimization.
In one particular example, the cool down simulation employs an ensemble that is at least one of an NVT ensemble, an NPT ensemble, and an NVE ensemble.
Optionally, the cooling speed of the cooling simulation is 1K/ps-20K/ps. For example, the cooling rate of the cooling simulation may be, but is not limited to, 1K/ps, 2K/ps, 5K/ps, 8K/ps, 10K/ps, 12K/ps, 15K/ps, 18K/ps, 20K/ps, etc.
Optionally, the initial temperature of the cooling simulation is 4000K to 5000K. For example, the initial temperature of the cooling simulation may be, but is not limited to, 4000K, 4100K, 4200K, 4300K, 4400K, 4500K, 4600K, 4700K, 4800K, 4900K, 5000K, etc.
Optionally, the temperature after the simulated temperature reduction is 250K to 350K. For example, the temperature after the simulated cooling may be, but is not limited to, 250K, 260K, 270K, 280K, 290K, 300K, 310K, 320K, 330K, 340K, 350K, etc. It is understood that the temperature after the cooling simulation cooling may be room temperature.
Optionally, the cooling time step of the cooling simulation is 1 fs/step to 5 fs/step. For example, the cooling time step of the cooling simulation may be, but is not limited to, 1 fs/step, 2 fs/step, 3 fs/step, 4 fs/step, 5 fs/step, etc.
Optionally, in the cooling simulation, when the temperature is reduced to the target temperature, the relaxation of 20ps to 50ps is performed at the target temperature. For example, the relaxation time may be, but is not limited to, 20ps, 25ps, 30ps, 35ps, 40ps, 45ps, 50ps, and the like. It can be understood that the target temperature is 250K to 350K when the temperature is reduced to the target temperature. For example, the target temperature may be, but is not limited to, 250K, 260K, 270K, 280K, 290K, 300K, 310K, 320K, 330K, 340K, 350K, and the like. It is understood that the target temperature may be room temperature. It is also understood that the target temperature is the temperature after the cool-down simulation cool-down.
In one specific example, the frequency of collecting the structural information within the box model is 100 steps/time to 1000 steps/time. Alternatively, the frequency of collecting the structural information within the cassette model is 100 steps/times, 200 steps/times, 300 steps/times, 400 steps/times, 500 steps/times, 600 steps/times, 700 steps/times, 800 steps/times, 900 steps/times, 1000 steps/times, etc.
In one specific example, the acquisition range is confirmed by potential functions including one or more of Lennard-Jones potential functions, morse potential functions, and Born-Mayer potential functions when acquiring structural information within the box model.
In one specific example, current performance parameters of the glass corresponding to the test components are calculated based on the structural information using one or more of VMD, OVITO, VESTA, and PIZZA.
It is understood that the configuration information includes information such as key length and key angle. It is also understood that chemical bonds include hydrogen bonds, metallic bonds, and the like. It is also understood that the performance parameters of the glass may be expressed as macroscopic performance parameters of the glass, such as hardness, visible light transmittance, and the like.
In a specific example, in step S102, after performing structure optimization on the box model, an optimized structure file may be output. Optionally, the output structure file is implemented using a translation command or translation software in a computer.
Yet another embodiment of the present application provides a method of making glass. The preparation method of the glass comprises the following steps: determining the target component of the glass by adopting the determination method; the glass is prepared with the target composition.
It is understood that in the glass production method, after the target components are determined, the glass can be produced by melting and shaping the target components. Optionally, the glass is ultra-white glass. Optionally, the glass is ultra-white float glass.
In one particular example, the target composition includes 68% to 78% SiO 2 0.1 to 3 percent of Al 2 O 3 11 to 18 percent of Na 2 O, 0 to 1% of K 2 O, 1.5 to 6.5 percent of MgO, 6.5 to 12 percent of CaO and less than or equal to 0.01 percent of Fe 2 O 3 . Alternatively, siO 2 、Al 2 O 3 、Na 2 The sum of the mass percentages of O, mgO and CaO is greater than or equal to 99%. Or,the test components also include K 2 O and/or Fe 2 O 3 . Optionally, in the glass, C1= O/Si is 1.1 to 4.6, C2= SiO 2 The ratio of/RO is 3.5-10.5, and C3= R 2 O/RO is 0.7-2.2, RO is MgO, caO, R 2 O is Na 2 O、K 2 O, C1, C2 and C3 represent mass ratios.
The following are specific examples.
Target compositions of the glasses obtained in examples 1 to 4 are shown in table 1, conditions in the glass composition determination process are shown in table 1, a box model is built by Materials Studio, and structural optimization is performed by Materials Studio. The box model of example 1 is shown in fig. 1, and the box model is a cube. The box model was a randomly distributed box containing 10000 atoms with a side length of 50.2 angstroms. The atom and structure information in the box model is shown in fig. 2, which contains chemical bond information such as bond length and bond angle, basic tetrahedral structural unit and connection information. The initial test component was 69.9% SiO 2 2.4% of Al 2 O 3 15.6% of Na 2 O, 0.5% of K 2 O, 5.4% MgO, 6.2% CaO and less than or equal to 0.01% Fe 2 O 3 。
TABLE 1
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is specific and detailed, but not to be understood as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the patent of the present invention should be subject to the appended claims, and the description and the drawings can be used for explaining the contents of the claims.
Claims (10)
1. A method for determining a glass composition, comprising the steps of:
step S101: establishing a box model of atoms of the test component;
step S102: carrying out structural optimization on the box model;
step S103: performing cooling simulation on the optimized box model based on molecular dynamics calculation, and acquiring structural information in the box model in the cooling simulation;
step S104: calculating the current performance parameters of the glass corresponding to the test components according to the structural information;
step S105: and comparing the current performance parameter with a target performance parameter, taking the test component as a target component when the current performance parameter meets the requirement of the target performance parameter, otherwise, adjusting the test component, repeating the steps S101-S104 by using the adjusted test component until the current performance parameter meets the requirement of the target performance parameter, and taking the adjusted test component as the target component.
2. A method for determining the composition of a glass as defined in claim 1, wherein the glass to which the test composition corresponds is a soda-lime-silica glass.
3. A method for determining the composition of glass according to claim 1, wherein said test composition comprises SiO 2 、Al 2 O 3 、Na 2 O, mgO, and CaO.
4. According to claim1, characterized in that the test component comprises 68 to 78 mass% of SiO 2 0.1 to 3 percent of Al 2 O 3 11 to 18 percent of Na 2 O, 0 to 1% of K 2 O, 1.5 to 6.5 percent of MgO, 6.5 to 12 percent of CaO and less than or equal to 0.01 percent of Fe 2 O 3 。
5. The method for determining glass composition according to any of claims 1 to 4, wherein the cassette model satisfies at least one of the following characteristics:
(1) Establishing the box model by one or more of Materials Studio, matlab, and LAMMPS;
(2) Establishing a boundary condition used by the box model as a periodic boundary condition and/or a fixed boundary condition;
(3) Establishing a force field type of the box model as CVFF and/or PVFF;
(4) The box model is in a cubic shape;
(5) The length of the single side of the box model is 47.2-51.4 angstroms;
(6) The density of atoms in the box model was 2.30g/cm 3 ～2.59g/cm 3 。
6. The method for determining glass composition according to any one of claims 1 to 4, wherein the structural optimization satisfies at least one of the following characteristics:
(1) The structural optimization is performed by one or more of Materials Studio, matlab, and LAMMPS;
(2) The structural optimization is geometric optimization;
(3) The structural optimization utilizes a gradient descent method, a conjugate gradient method or a steepest descent method for energy minimization.
7. The method for determining glass composition according to any one of claims 1 to 4, wherein the cooling simulation satisfies at least one of the following characteristics:
(1) An ensemble adopted by the cooling simulation is at least one of an NVT ensemble, an NPT ensemble and an NVE ensemble;
(2) The cooling speed of the cooling simulation is 1K/ps-20K/ps;
(3) The initial temperature of the cooling simulation is 4000K-5000K, and the temperature after the cooling simulation is 250K-350K;
(4) The step length of the cooling time of the cooling simulation is 1 fs/step to 5 fs/step;
(5) In the cooling simulation, when the temperature is reduced to the target temperature, the relaxation of 20ps to 50ps is carried out at the target temperature.
8. The method for determining glass composition according to any one of claims 1 to 4, wherein the structural information in the collected cassette model satisfies at least one of the following characteristics:
(1) The frequency of collecting the structural information in the box model is 100 steps/time to 1000 steps/time;
(2) The acquisition range is confirmed by potential functions including one or more of a Lennard-Jones potential function, a Morse potential function, and a Born-Mayer potential function when acquiring the structural information within the box model.
9. A method according to any one of claims 1 to 4, wherein the calculation of the current performance parameters of the glass corresponding to the test components from the structural information is performed using one or more of VMD, OVITO, VESTA and PIZZA.
10. A glass preparation method is characterized by comprising the following steps:
determining a target component of the glass by the determination method according to any one of claims 1 to 9;
the glass is prepared with the target composition.
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| CN108585478A (en) * | 2018-07-11 | 2018-09-28 | 北京建筑大学 | Vehicle glass based on uniform design and preparation method |
| CN110021380A (en) * | 2019-04-25 | 2019-07-16 | 济南大学 | A method of each atom scattering nature in glass system is probed into based on molecular dynamics simulation |
| CN110648727A (en) * | 2019-10-30 | 2020-01-03 | 华南理工大学 | Preparation method of glass material with specific physical properties |
| CN112592055A (en) * | 2020-12-24 | 2021-04-02 | 沙河市禾木新能源有限公司 | Ultrathin sodium-calcium silicate glass and preparation method thereof |
| CN113012764A (en) * | 2021-03-05 | 2021-06-22 | 华南理工大学 | Bioactive glass structure based on molecular dynamics and simulation method of XRD calculation |
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108585478A (en) * | 2018-07-11 | 2018-09-28 | 北京建筑大学 | Vehicle glass based on uniform design and preparation method |
| CN110021380A (en) * | 2019-04-25 | 2019-07-16 | 济南大学 | A method of each atom scattering nature in glass system is probed into based on molecular dynamics simulation |
| CN110648727A (en) * | 2019-10-30 | 2020-01-03 | 华南理工大学 | Preparation method of glass material with specific physical properties |
| CN112592055A (en) * | 2020-12-24 | 2021-04-02 | 沙河市禾木新能源有限公司 | Ultrathin sodium-calcium silicate glass and preparation method thereof |
| CN113012764A (en) * | 2021-03-05 | 2021-06-22 | 华南理工大学 | Bioactive glass structure based on molecular dynamics and simulation method of XRD calculation |
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