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Elastic modulus prediction method based on molecular dynamics and elastic network regression model

A technology of molecular dynamics and elastic modulus, which is applied in prediction, special data processing applications, data processing applications, etc., can solve problems such as the inability to predict the elastic modulus of glass intuitively, quickly and accurately, and achieve short training model time and system The effect of simple structure and simplified calculation process

Active Publication Date: 2021-08-13
NANJING FIBERGLASS RES & DESIGN INST CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0005] In order to solve the problem that the prior art cannot intuitively, quickly and accurately predict the elastic modulus of glass, the present invention provides a method for predicting the elastic modulus based on molecular dynamics and elastic network regression models, the method comprising:

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  • Elastic modulus prediction method based on molecular dynamics and elastic network regression model
  • Elastic modulus prediction method based on molecular dynamics and elastic network regression model
  • Elastic modulus prediction method based on molecular dynamics and elastic network regression model

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Embodiment 1

[0063] This embodiment provides a method for predicting elastic modulus based on molecular dynamics and elastic network regression algorithm, see figure 1 , the method includes:

[0064] Step 1, collect elastic modulus data of glass materials with different components, and construct an elastic modulus database, which includes one-to-one mapped glass components and their corresponding elastic moduli;

[0065] Step 2. Construct the descriptor of the elastic modulus of the oxide glass material containing the "material gene" based on molecular dynamics, see figure 2 ;

[0066] 2-1 Construct atomic structure models of oxide crystals with different symmetries as unit cells for molecular dynamics calculations;

[0067] 2-2 For each unit cell structure constructed in step 2-1, perform molecular dynamics calculations to obtain the optimized unit cell energy ;

[0068] 2-3 Aiming at the structure of the above-mentioned crystals with various symmetries optimized by molecular dynam...

Embodiment 2

[0082] The present embodiment provides a method for predicting elastic modulus based on molecular dynamics and elastic network regression algorithm, the method comprising:

[0083] Step 1, collect elastic modulus data of glass materials with different components, and construct an elastic modulus database, which includes one-to-one mapped glass components and their corresponding elastic moduli;

[0084] For the collected elastic modulus data, in practical application, it also includes preprocessing, and the preprocessing includes:

[0085] For any pair of glass components, judge whether the following two conditions are true at the same time:

[0086] Condition 1: In the glass composition, the molar ratio difference of each oxide component is less than or equal to the first preset threshold, and the unit is percentage;

[0087] Condition 2: the difference between the elastic moduli of the two glasses is greater than a second preset threshold, and the unit is a percentage;

[0...

Embodiment 3

[0177] The present embodiment provides a system for predicting elastic modulus based on molecular dynamics and elastic network regression algorithm, the system comprising:

[0178] The elastic modulus database construction module is used to collect the elastic modulus data of glass materials with different components, and construct the elastic modulus database, which includes one-to-one mapped glass components and their corresponding elastic moduli;

[0179] Descriptor building blocks for constructing descriptors containing "material genes" for the elastic modulus of oxide glass materials based on molecular dynamics;

[0180] The training data building block is used to build a training set, a verification set and a test set based on the elastic modulus database constructed by the elastic modulus database building block and the descriptor constructed by the descriptor building block;

[0181] The model construction training module is used to construct the elastic modulus predic...

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Abstract

The invention discloses an elastic modulus prediction method based on molecular dynamics and an elastic network regression model, and belongs to the field of glass performance prediction. Crystal and non-crystal structures of oxides in the glass are established based on molecular dynamics, long-range disorder and short-range orderliness of the glass are considered, the method better conforms to actual glass rules, and the elasticity modulus of the glass performance is improved. Binding energy of unit cations in a crystal, an elastic tensor constant of a unit cell and a product of a bulk modulus and a shear modulus of the unit cell are innovatively put forward as performance parameters, and a descriptor used in an elastic network regression model is correspondingly constructed, so that accurate prediction of the elastic modulus of the glass is realized; and the descriptors are calculated based on molecular dynamics, the Newton's law is based, the system structure is simple, the behavior of each electron does not need to be considered, an electronic mechanism of the system is equivalent to a potential energy function in atoms, the calculation process is greatly simplified, and the calculation time is saved.

Description

technical field [0001] The invention relates to an elastic modulus prediction method based on molecular dynamics and an elastic network regression model, belonging to the field of glass performance prediction. Background technique [0002] The elastic modulus is an important performance parameter of engineering materials. From a macroscopic point of view, the elastic modulus is a measure of the ability of an object to resist elastic deformation. From a microscopic point of view, it is the bond strength between atoms, ions or molecules. reflect. All factors that affect the bonding strength can affect the elastic modulus of the material, such as bonding mode, crystal structure, chemical composition, microstructure, temperature, etc. The elastic modulus can be regarded as an index to measure the difficulty of elastic deformation of the material. The larger the value, the greater the stress that causes the material to undergo a certain elastic deformation, that is, the greater ...

Claims

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Application Information

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IPC IPC(8): G06F30/17G06F30/27G06Q10/04
CPCG06Q10/04G06F30/17G06F30/27
Inventor 赵明赵谦刘鑫陈阳匡宁
Owner NANJING FIBERGLASS RES & DESIGN INST CO LTD
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