A polymer physical property prediction device includes a processor, and a memory storing program instructions that cause the processor to read a structural unit from a storage unit and use the structural unit to calculate numbers each indicating how many substructures are in a polymer, the polymer being formed of repetition of the structural unit, calculate a number indicating how many atoms are in the structural unit, calculate number densities of the substructures from the numbers of substructures and the number of atoms in the structural unit, construct a regression model that predicts a physical property value by using an experimental value of a physical property of the polymer and the number densities of the substructures, input a polymer structure of which the physical property value is to be predicted, and predict the physical property value corresponding to the input polymer structure by using the regression model.
Legal claims defining the scope of protection, as filed with the USPTO.
2. The polymer physical property prediction device as claimed in claim 1, wherein the program instructions cause the processor to further classify the substructures of the polymer using an algorithm, and the calculated numbers of substructures each indicate a number of each corresponding classified substructure present in the polymer.
3. The polymer physical property prediction device as claimed in claim 1, wherein the program instructions cause the processor to further remove part of the calculated number densities of the substructures.
4. The polymer physical property prediction device as claimed in claim 1, wherein the program instructions cause the processor to further generate a model structure by repeatedly using the structural unit obtained from the storage unit.
6. The polymer physical property prediction device as claimed in claim 1, wherein the program instructions cause the processor to calculate the numbers of substructures and the number of atoms in the polymer structure by using the input polymer structure, calculate the number densities of the substructures from the calculated numbers of substructures and the calculated number of atoms, and apply the calculated number densities to the constructed regression model to predict the physical property value of the polymer structure.
7. The polymer physical property prediction device as claimed in claim 1, wherein the physical property value is a value of a refractive index or a value of a glass transition point.
8. The polymer physical property prediction device as claimed in claim 1, wherein the physical property value is a value of a band gap, a value of a relative permittivity, a value of a coefficient of linear expansion, or a value of a density.
9. The polymer physical property prediction device as claimed in claim 1, wherein the numbers each indicating how many substructures are in the polymer are calculated by counting a substructure in the polymer to obtain a substructure number indicating how many units of the substructure are in the polymer, a number of atoms in the polymer is calculated, and the number densities are calculated by dividing the substructure number by the number of atoms in the polymer.
10. The polymer physical property prediction device as claimed in claim 3, wherein the program instructions cause the processor to calculate the numbers of substructures and the number of atoms of the polymer structure by using the input polymer structure, calculate the number densities of the substructures from the calculated numbers of substructures and the calculated number of atoms, remove part of the calculated number densities of the substructures, and apply the number densities whose part is removed to the constructed regression model to predict the physical property value of the polymer structure.
11. The polymer physical property prediction device as claimed in claim 4, wherein the program instructions cause the processor to generate an input polymer model structure by repeatedly using the input polymer structure, calculate the numbers of substructures and the number of atoms in the input polymer model structure, calculate the number densities of the substructures from the calculated numbers of substructures and the calculated number of atoms, and apply the calculated number densities to the constructed regression model to predict the physical property value of the polymer structure.
12. The polymer physical property prediction device as claimed in claim 5, wherein the program instructions cause the processor to generate the model structure by repeatedly using the input polymer structure, calculate the numbers of substructures and the number of atoms in the model structure, calculate the number densities of the substructures from the calculated numbers of substructures and the calculated number of atoms, remove the part of the structure descriptor representing the calculated number densities of the substructures, and apply the number densities whose part is removed to the constructed regression model to predict the physical property value of the polymer structure.
14. The recording medium as claimed in claim 13, wherein the predicting the physical property value further includes calculating the numbers of substructures and the number of atoms in the polymer structure by using the input polymer structure, calculating the number densities of the substructures from the calculated numbers of substructures and the calculated number of atoms, and applying the calculated number densities to the regression model to predict the physical property value of the polymer structure.
15. The non-transitory computer-readable recording medium as claimed in claim 13, wherein the numbers each indicating how many substructures are in the polymer are calculated by counting a substructure in the polymer to obtain a substructure number indicating how many units of the substructure are in the polymer, a number of atoms in the polymer is calculated, and the number densities are calculated by dividing the substructure number by the number of atoms in the polymer.
17. The polymer physical property prediction method as claimed in claim 16, wherein the predicting the physical property value further includes calculating the numbers of substructures and the number of atoms in the polymer structure by using the input polymer structure, calculating the number densities of the substructures from the calculated numbers of substructures and the calculated number of atoms, and applying the calculated number densities to the regression model to predict the physical property value of the polymer structure.
18. The polymer physical property prediction method as claimed in claim 16, wherein the numbers each indicating how many substructures are in the polymer are calculated by counting a substructure in the polymer to obtain a substructure number indicating how many units of the substructure are in the polymer, a number of atoms in the polymer is calculated, and the number densities are calculated by dividing the substructure number by the number of atoms in the polymer.
20. The polymer manufacturing method as claimed in claim 19, wherein the numbers each indicating how many substructures are in the polymer are calculated by counting a substructure in the polymer to obtain a substructure number indicating how many units of the substructure are in the polymer, a number of atoms in the polymer is calculated, and the number densities are calculated by dividing the substructure number by the number of atoms in the polymer.
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September 1, 2020
February 27, 2024
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