CN115536269B - 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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- CN115536269B CN115536269B CN202211318600.3A CN202211318600A CN115536269B CN 115536269 B CN115536269 B CN 115536269B CN 202211318600 A CN202211318600 A CN 202211318600A CN 115536269 B CN115536269 B CN 115536269B
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- 239000011521 glass Substances 0.000 title claims abstract description 105
- 238000000034 method Methods 0.000 title claims abstract description 41
- 238000004519 manufacturing process Methods 0.000 title claims description 14
- 238000012360 testing method Methods 0.000 claims abstract description 66
- 238000001816 cooling Methods 0.000 claims abstract description 43
- 238000004088 simulation Methods 0.000 claims abstract description 35
- 239000000463 material Substances 0.000 claims abstract description 15
- 238000004364 calculation method Methods 0.000 claims abstract description 8
- 238000000329 molecular dynamics simulation Methods 0.000 claims abstract description 8
- 239000000203 mixture Substances 0.000 claims description 25
- 238000005457 optimization Methods 0.000 claims description 17
- 229910018072 Al 2 O 3 Inorganic materials 0.000 claims description 14
- 229910004298 SiO 2 Inorganic materials 0.000 claims description 10
- 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
- 238000002945 steepest descent method Methods 0.000 claims description 3
- 238000002834 transmittance Methods 0.000 claims description 3
- 238000002360 preparation method Methods 0.000 abstract description 4
- 230000008569 process Effects 0.000 abstract description 3
- 239000002699 waste material Substances 0.000 abstract description 3
- 239000005329 float glass Substances 0.000 description 12
- 239000000126 substance Substances 0.000 description 4
- 230000003247 decreasing effect Effects 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 239000005361 soda-lime glass Substances 0.000 description 2
- ATJFFYVFTNAWJD-UHFFFAOYSA-N Tin Chemical compound [Sn] ATJFFYVFTNAWJD-UHFFFAOYSA-N 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 239000013078 crystal Substances 0.000 description 1
- 238000005520 cutting process Methods 0.000 description 1
- 238000010586 diagram 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
- 230000003993 interaction Effects 0.000 description 1
- 238000002844 melting Methods 0.000 description 1
- 230000008018 melting Effects 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 229910052751 metal Inorganic materials 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
- 230000009467 reduction Effects 0.000 description 1
- 238000007493 shaping process Methods 0.000 description 1
- 238000013519 translation Methods 0.000 description 1
Classifications
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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
-
- 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
-
- 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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- Engineering & Computer Science (AREA)
- Chemical & Material Sciences (AREA)
- Theoretical Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Computing Systems (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Crystallography & Structural Chemistry (AREA)
- Chemical Kinetics & Catalysis (AREA)
- General Chemical & Material Sciences (AREA)
- Geochemistry & Mineralogy (AREA)
- Materials Engineering (AREA)
- Organic Chemistry (AREA)
- Glass Compositions (AREA)
Abstract
The invention relates to a method for determining a glass component and a glass preparation method. The method for determining the glass component mainly comprises the steps of establishing 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 the current performance of glass corresponding to the test component according to the structural information, and comparing the current performance parameter with a target performance parameter. In the determination method, test glass does not need to be manufactured, material waste in the component determination process can be effectively reduced, and a new thought is provided for determining the components of the glass.
Description
Technical Field
The invention relates to the technical field of glass research, in particular to a method for determining glass components and a glass preparation method.
Background
With the continuous and deep research on glass, the variety and the performance of the glass are greatly enriched. Researchers can design corresponding glass according to the actual use requirements of the glass. In the design of glass, the glass composition is one of the important factors that determine the properties of the glass. In the process of determining the glass components, conventionally, different glass components are designed, then the glass components are manufactured into test glass, then the performance of the test glass is tested, then whether the performance of the glass can meet the requirements is evaluated, and then the components of the glass are determined according to the performance evaluation result of the glass. The method has better intuitiveness and better guiding significance for determining the glass components. However, this method requires preparing more test glass for performance testing, and thus consumes more testing time and results in greater material wastage.
Disclosure of Invention
Based on this, it is necessary to provide a method for determining a glass composition and a glass production method capable of reducing waste of materials.
In order to solve the technical problems, the technical scheme of the application is as follows:
a method of determining a glass composition comprising the steps of:
step S101: establishing a box model of atoms of the test component;
step S102: performing 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: comparing the current performance parameter with a target performance parameter, when the current performance parameter meets the requirement of the target performance parameter, taking the test component as a target component, otherwise, adjusting the test component, repeating the steps S101-S104 with 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 corresponding to the test component is 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 to 78 mass percent of SiO 2 0.1 to 3 percent of Al 2 O 3 11% -18% of Na 2 O, 0-1% of K 2 O, mgO of 1.5-6.5%, caO of 6.5-12% and Fe of less than or equal to 0.01% 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 build the box model are periodic boundary conditions and/or fixed boundary conditions.
In one embodiment, the field type establishing the box model is CVFF and/or PVFF.
In one embodiment, the shape of the box model is a cube shape.
In one embodiment, the length of a single side of the cassette model is 47.2 angstroms to 51.4 angstroms.
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 a 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 cooling time step 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 a target temperature, relaxation of 20ps to 50ps is performed at the target temperature.
In one embodiment, the frequency of collecting structural information within the box model is 100 steps/time to 1000 steps/time.
In one embodiment, the collection range is confirmed by a potential function when collecting structural information within the box model, the potential function including one or more of a Lennard-Jones potential function, a Morse potential function, and a Born-Mayer potential function.
In one embodiment, the current performance parameters of the glass corresponding to the test components are calculated from the structural information using one or more of VMD, OVITO, VESTA and PIZZA.
A method of making glass comprising the steps of:
determining a target composition of the glass using the determination method described in any of the embodiments above;
and preparing glass with the target component.
The method for determining the glass component 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, comparing the current performance parameter with a target performance parameter, when the current performance parameter meets the requirement of the target performance parameter, taking the test component as the target component, otherwise, adjusting the test component, repeatedly establishing the 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 component can be obtained on the molecular level, and the adjustment of the glass component is guided according to the calculated performance parameter, so that the glass component meeting the requirement of the target performance parameter is obtained.
Drawings
Fig. 1 is a schematic diagram of a box model in example 1 of the present application.
FIG. 2 is a schematic representation of atomic and chemical information in the cassette model of example 1 of the present application.
Detailed Description
In order that the above objects, features and advantages of the invention will be readily understood, a more particular description of the invention will be rendered by reference to the appended drawings. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. The present invention may be embodied in many other forms than described herein and similarly modified by those skilled in the art without departing from the spirit of the invention, whereby the invention is not limited to the specific embodiments disclosed below.
In the present invention, unless explicitly specified and limited otherwise, the terms "mounted," "connected," "secured," and the like are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally formed; can be mechanically or electrically connected; either directly or indirectly, through intermediaries, or both, may be in communication with each other or in interaction with each other, unless expressly defined otherwise. The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art according to the specific circumstances.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present invention, the meaning of "plurality" means at least two, for example, two, three, etc., unless specifically defined 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 herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
An 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 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 collecting 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: comparing the current performance parameter with the target performance parameter, when the current performance parameter meets the requirement of the target performance parameter, taking the test component as the target component, otherwise, adjusting the test component, repeating the steps S101-S104 with 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 a glass component mainly includes the steps of establishing 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, when the current performance parameter meets requirements of the target performance parameter, taking the test component as the target component, otherwise, adjusting the test component, repeating the steps of establishing the box model-structural optimization-cooling simulation with the adjusted test component, collecting structural information-calculating the current performance parameter until the current performance parameter meets requirements 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 component can be obtained on the molecular level, and the adjustment of the glass component is guided according to the calculated performance parameter, so that the glass component meeting the requirement of the target performance parameter is obtained. In addition, the determination method in the embodiment is adopted to confirm the glass components, so that compared with the traditional method for manufacturing test glass, the method is time-saving and labor-saving, saves cost and has higher efficiency.
It is understood that in the above-described method for determining a glass composition, when the current performance parameter does not meet the requirement of the target performance parameter in step S105, the manner of adjusting the test composition may be to adjust the ratio of each component in the test composition, for example, to adjust the mass percentage of each component in the test composition. In adjusting the test components, the adjustment directions of the respective component ratios in the test components may be the same or different. For example, when adjusting the test components, the ratio of the components in the test components may be adjusted in the increasing direction at the same time, may be adjusted in the decreasing direction at the same time, or may be adjusted in the increasing direction partially or in the decreasing direction partially.
In a specific example, the above method of determining the composition of glass is applicable to the determination of the composition of ultrawhite glass. The ultra-white glass generally refers to glass with visible light transmittance higher than 91%, has crystal clear characteristic and is widely applied to the fields of solar photovoltaics, cars, buildings, gardening, furniture and the like. With the continuous increase of the consumption demand, the demand and the application range of the ultra-white glass are continuously increased. The method for determining the glass components can be used for determining the components of the ultra-white glass relatively quickly, so that the production of the ultra-white glass is guided, the production efficiency of the ultra-white glass is improved, the waste of materials in the preparation process of the ultra-white glass is reduced, and the material cost of the ultra-white glass is reduced.
Further, the above method for determining the composition of glass is applicable to the determination of the composition of ultra-white float glass. Float glass has many advantages such as high transparency, smooth hand feel, good flatness, easy cutting, etc. Float glass, however, also differs from a particular glass production process in that the forming process is usually carried out in a tin bath through which a shielding gas is introduced. This indicates that float glass has a certain specificity in the manufacturing process, where more time and materials may be consumed if the composition of the glass is determined in a conventional manner for manufacturing test glass, testing the properties of the glass. The method for determining the components of the ultra-white float glass is adopted to determine the components of the ultra-white float glass, so that test glass does not need to be prepared for testing, the components of the ultra-white float glass can be determined relatively quickly, the production of the ultra-white float glass is guided, the material cost of the ultra-white float glass is reduced, and the processing efficiency of the ultra-white float glass is improved.
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 a specific example, the glass corresponding to the test composition is soda lime silica glass.
In one specific example, the test component comprises SiO 2 、Al 2 O 3 、Na 2 O, mgO and CaO. Optionally, in the test component, siO 2 、Al 2 O 3 、Na 2 O, mgO and CaO in mass percentAnd 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 component, c1=o/Si is 1.1 to 4.6, c2=sio 2 RO is 3.5 to 10.5, 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, C3 represent mass ratios.
In one specific 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 O, mgO and CaO are added to be greater than or equal to 99% by mass. Optionally, the target component further comprises K 2 O and/or Fe 2 O 3 . Alternatively, in the target component, c1=o/Si is 1.1 to 4.6, c2=sio 2 RO is 3.5 to 10.5, 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, C3 represent mass ratios.
Optionally, the test component comprises 68-78% of SiO by mass percent 2 0.1 to 3 percent of Al 2 O 3 11% -18% of Na 2 O, 0-1% of K 2 O, mgO of 1.5-6.5%, caO of 6.5-12% and Fe of less than or equal to 0.01% 2 O 3 。
In one specific example, the target composition includes 68% to 78% SiO 2 0.1 to 3 percent of Al 2 O 3 11% -18% of Na 2 O, 0-1% of K 2 O, mgO of 1.5-6.5%, caO of 6.5-12% and Fe of less than or equal to 0.01% 2 O 3 。
In yet another embodiment, a glass is provided having a composition comprising, by mass, 68% to 78% SiO 2 0.1 to 3 percent of Al 2 O 3 11% -18% of Na 2 O, 0-1% of K 2 O, mgO of 1.5-6.5%, caO of 6.5-12% and Fe of less than or equal to 0.01% 2 O 3 . Optionally, the glassThe composition of the glass is determined by the determination method of the glass composition. Further, in glass, siO 2 、Al 2 O 3 、Na 2 O, mgO and CaO are added to be greater than or equal to 99% by mass. Optionally, the test component further comprises K 2 O and/or Fe 2 O 3 . Alternatively, in glass, c1=o/Si is 1.1 to 4.6, c2=sio 2 RO is 3.5 to 10.5, 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, C3 represent mass ratios. Optionally, the glass is an ultrawhite glass. Alternatively, the glass is ultra-white float glass.
It will be appreciated that SiO 2 The mass percentages of (a) may be, but are not limited to 68%, 69%, 70%, 71%, 72%, 73%, 74%, 75%, 76%, 77%, 78%, etc. Al (Al) 2 O 3 The mass percentage of (c) 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 (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 (Fe) 2 O 3 The mass percentage of (a) 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 method of determining the glass composition, a box model is established by one or more of Materials Studio, matlab, and LAMMPS. Boundary for building box modelThe conditions are periodic boundary conditions and/or fixed boundary conditions. The field type of the established box model is CVFF and/or PVFF. The shape of the box model is a cubic shape, for example, the shape of the box model may be a cuboid, a cube, or the like. Alternatively, the length of the single side of the box model is 47.2 to 51.4 angstroms (1 angstrom=0.1 nm), and the single side length of the box model may be determined to be 47.2 to 51.4 angstroms according to the number of atoms in the box model. For example, when the number of atoms in the box model is 8000 to 10000, the single-side length of the box model is 47.2 to 51.4 angstroms. Alternatively, the box model is a cube with a side length of 47.2 angstroms to 51.4 angstroms. Alternatively, the density of atoms in the cassette 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 Etc.
In one specific example, the structural optimization is performed by one or more of Materials Studio, matlab, and LAMMPS. Optionally, the structural optimization is a geometric optimization. Further alternatively, the structural optimization utilizes a gradient descent method, a conjugate gradient method, or a steepest descent method for energy minimization.
In one specific example, the ensemble employed for the cooling simulation 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-5000K. For example, the initial temperature of the cool down 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 temperature reduction simulation is 250K to 350K. For example, the temperature after the cooling simulation 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 simulated cooling down may be room temperature.
Optionally, the cooling time step of the cooling simulation is 1 fs/step-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 lowered to the target temperature, 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, etc. It is 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 cooling simulation.
In one specific example, the frequency of collecting structural information within the box model is 100 steps/time to 1000 steps/time. Optionally, the frequency of collecting structural information within the box model is 100 steps/time, 200 steps/time, 300 steps/time, 400 steps/time, 500 steps/time, 600 steps/time, 700 steps/time, 800 steps/time, 900 steps/time, 1000 steps/time, etc.
In one specific example, the collection range is confirmed by a potential function when collecting structural information within the box model, the potential function including one or more of a Lennard-Jones potential function, a Morse potential function, a Born-Mayer potential function.
In one specific example, calculating the current performance parameters of the glass corresponding to the test components based on the structural information is performed using one or more of VMD, OVITO, VESTA and PIZZA.
It is understood that the structural information includes information such as key length and key angle. It is also understood that chemical bonds include hydrogen bonds, metal 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, etc.
In a specific example, in step S102, after the box model is structurally optimized, an optimized structure file may be output. Alternatively, the output structure file is implemented using a translation command or translation software in the computer.
Yet another embodiment of the present application provides a method of making glass. The glass preparation method comprises the following steps: determining a target component of the glass by the determination method; glass is prepared with the target component.
It will be appreciated that in the glass manufacturing method, after the target component is determined, the glass may be manufactured by melting and shaping the target component. Alternatively, the glass is an ultrawhite glass. Alternatively, the glass is ultra-white float glass.
In one specific example, the target composition includes 68% to 78% SiO 2 0.1 to 3 percent of Al 2 O 3 11% -18% of Na 2 O, 0-1% of K 2 O, mgO of 1.5-6.5%, caO of 6.5-12% and Fe of less than or equal to 0.01% 2 O 3 . Alternatively, siO 2 、Al 2 O 3 、Na 2 O, mgO and CaO are added to be greater than or equal to 99% by mass. Optionally, the test component further comprises K 2 O and/or Fe 2 O 3 . Alternatively, in glass, c1=o/Si is 1.1 to 4.6, c2=sio 2 RO is 3.5 to 10.5, 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, C3 represent mass ratios.
The following are specific examples.
The objective compositions of the glasses obtained in examples 1 to 4 are shown in Table 1, the conditions in the determination of the glass compositions are shown in Table 1, a box model is built by means of Materials Studio, and structural optimization is performed by means of 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. Atomic and structural information in a box modelFIG. 2 shows that the information of chemical bonds such as bond lengths and bond angles, basic tetrahedral structural units, and connection information are contained therein. The initial test component was 69.9% SiO 2 2.4% Al 2 O 3 15.6% Na 2 O, 0.5% 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 above-described embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above-described embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the invention, which are described in detail and are not to be construed as limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. The scope of the invention is therefore intended to be covered by the appended claims, and the description and drawings may be interpreted in accordance with 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: performing 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: comparing the current performance parameter with a target performance parameter, when the current performance parameter meets the requirement of the target performance parameter, taking the test component as a target component, otherwise, adjusting the test component, repeating the steps S101-S104 with 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;
wherein the test component comprises 68-78% of SiO 2 0.1 to 3 percent of Al 2 O 3 11% -18% of Na 2 O, 0-1% of K 2 O, mgO of 1.5-6.5%, caO of 6.5-12% and Fe of less than or equal to 0.01% 2 O 3 ；
In the test component, c1=o/Si is 1.1 to 4.6, c2=sio 2 RO is 3.5 to 10.5, 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 ratio;
the cooling speed of the cooling simulation is 1K/ps-20K/ps;
the frequency of collecting the structure information in the box model is 100 steps/time to 1000 steps/time;
confirming an acquisition range through a potential function when acquiring structural information in a box model, wherein the potential function comprises one or more of a Lennard-Jones potential function, a Morse potential function and a Bern-Mayer potential function;
the target performance parameters include: hardness of not less than 524kgf/mm 2 The visible light transmittance is more than or equal to 91.4 percent.
2. The method of claim 1, wherein the cassette model is created by one or more of Materials Studio, matlab, and LAMMPS.
3. The method of claim 1, wherein the boundary conditions used to build the box model are periodic boundary conditions and/or fixed boundary conditions.
4. The method of claim 1, wherein the force field type modeling the box is CVFF and/or PVFF.
5. The method of any one of claims 1 to 4, wherein the cassette model satisfies at least one of the following characteristics:
(1) The box model is cube-shaped;
(2) The length of a single side of the box model is 47.2-51.4 angstroms;
(3) The density of atoms in the box model was 2.30g/cm 3 ～2.59g/cm 3 。
6. The method of 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 of any one of claims 1 to 4, wherein the cooling simulation satisfies at least one of the following characteristics:
(1) The ensemble adopted in the cooling simulation is at least one of an NVT ensemble, an NPT ensemble and an NVE ensemble;
(2) The initial temperature of the cooling simulation is 4000K-5000K, and the temperature after the cooling simulation is 250K-350K;
(3) The cooling time step of the cooling simulation is 1 fs/step-5 fs/step.
8. The method according to any one of claims 1 to 4, wherein in the cooling simulation, when cooling to a target temperature, relaxation of 20ps to 50ps is performed at the target temperature.
9. The method according to any one of claims 1 to 4, wherein calculating the current performance parameter of the glass corresponding to the test component based on the structural information is performed using one or more of VMD, OVITO, VESTA and PIZZA.
10. A method for producing glass, comprising the steps of:
determining a target composition of glass using the determination method according to any one of claims 1 to 9;
and preparing glass with the target component.
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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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