Database, material data processing system, and method of creating database
A database storing data associated with an identifier unique to each sample, the data including first data representative of at least one of composition data, processing data, and property data for the each sample, and second data representative of microstructure data for the each sample. The microstructure data includes a feature determined based on a temperature dependence of magnetization for the each sample.
1. A material designing apparatus for designing a target material, the material designing apparatus comprising a data processing device configured to:
retrieve data from a database storing the data, the data including:
first data representative of at least one of composition data, processing data, and property data of each sample, and
second data representative of microstructure data of each sample, the microstructure data including a feature determined based on a magnetization temperature dependence of each sample,
create a mathematical model based on the first data and the second data, and
determine a variable defining at least one of composition, processing, property, and microstructure of the target material.
2. The material designing apparatus of claim 1 , wherein:
the first data includes, as the composition data, a type of elements contained in each sample and a composition ratio of the elements, and
the first data includes, as the processing data, a parameter that defines a condition of a heat treatment performed in a step of producing each sample.
3. The material designing apparatus of claim 1 , wherein:
the first data includes, as the property data, at least one of a residual magnetic flux density, coercivity, magnetic saturation, and magnetic permeability of each sample.
4. The material designing apparatus of claim 1 , wherein:
the second data includes, as the microstructure data, a parameter that defines a crystal structure of a primary phase contained in each sample.
5. The material designing apparatus of claim 1 , wherein:
the mathematical model includes the variable defining the at least one of composition, processing, and property as an objective variable, and includes the feature determined based on the magnetization temperature dependence as an explanatory variable that defines the microstructure.
6. The material designing apparatus of claim 1 , wherein:
the feature determined based on the magnetization temperature dependence is a feature regarding a magnetic phase transition.
7. The material designing apparatus of claim 6 , wherein:
the feature regarding the magnetic phase transition includes at least one of a Curie temperature and a Néel temperature.
8. The material designing apparatus of claim 1 , wherein:
the data stored in the database is collected from a plurality of companies and is managed as big data, the database is configured to allow the plurality of companies to access to the database.
9. A computer-implemented method of developing materials using materials informatics, the method comprising:
retrieving data from a database by a data processing device, the data including:
first data representative of at least one of composition data, processing data, and property data of each sample, and
second data representative of microstructure data of each sample, the microstructure data including a feature determined based on a magnetization temperature dependence of each sample,
creating a mathematical model, based on the first data and the second data, by the data processing device, and
determining a variable defining at least one of composition, processing, property, and microstructure of the target material by the data processing device.
10. The method of claim 9 , wherein:
the mathematical model includes the variable defining the at least one of composition, processing, and property as an objective variable, and includes the feature determined based on the magnetization temperature dependence as an explanatory variable that defines the microstructure.
11. The method of claim 9 , wherein:
the data stored in the database is collected from a plurality of companies and is managed as big data, the database is configured to allow the plurality of companies to access to the database.