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Informatics derived materials databases for multifunctional properties

View Article: PubMed Central - PubMed

ABSTRACT

In this review, we provide an overview of the development of quantitative structure–property relationships incorporating the impact of data uncertainty from small, limited knowledge data sets from which we rapidly develop new and larger databases. Unlike traditional database development, this informatics based approach is concurrent with the identification and discovery of the key metrics controlling structure–property relationships; and even more importantly we are now in a position to build materials databases based on design ‘intent’ and not just design parameters. This permits for example to establish materials databases that can be used for targeted multifunctional properties and not just one characteristic at a time as is presently done. This review provides a summary of the computational logic of building such virtual databases and gives some examples in the field of complex inorganic solids for scintillator applications.

No MeSH data available.


Definition of lower approximation, upper approximation, and boundary region for very high light yield compounds is shown. The lower approximation is defined as the region where every compound is within the same class, in this case very high light yield. The upper approximation is then the region which contains that class while also some compounds in other classes. The boundary region is defined as the region in between the lower and upper approximation. By introducing this boundary region, where compounds may possibly belong to a class, we introduce uncertainty into the analysis.
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Figure 3: Definition of lower approximation, upper approximation, and boundary region for very high light yield compounds is shown. The lower approximation is defined as the region where every compound is within the same class, in this case very high light yield. The upper approximation is then the region which contains that class while also some compounds in other classes. The boundary region is defined as the region in between the lower and upper approximation. By introducing this boundary region, where compounds may possibly belong to a class, we introduce uncertainty into the analysis.

Mentions: We define two further parameters: the lower approximation and the upper approximation where X is a subset of U. Effectively, we can consider this as defining the range of descriptor values where every entry belongs to a specific class/category and the range which contains all the values of a class/category. In this way, every entry within the lower approximation material belongs to the same class, while in the upper approximation, all materials of a class are contained, while at the same time materials of other classes may also be present. In a situation where all compounds of a class were clustered together in the attribute space, the lower and upper approximations would be equal. The definition of the boundary region for low LY compounds within B = (density, EC factor) for very high LY compounds is provided in figure 3.


Informatics derived materials databases for multifunctional properties
Definition of lower approximation, upper approximation, and boundary region for very high light yield compounds is shown. The lower approximation is defined as the region where every compound is within the same class, in this case very high light yield. The upper approximation is then the region which contains that class while also some compounds in other classes. The boundary region is defined as the region in between the lower and upper approximation. By introducing this boundary region, where compounds may possibly belong to a class, we introduce uncertainty into the analysis.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC5036495&req=5

Figure 3: Definition of lower approximation, upper approximation, and boundary region for very high light yield compounds is shown. The lower approximation is defined as the region where every compound is within the same class, in this case very high light yield. The upper approximation is then the region which contains that class while also some compounds in other classes. The boundary region is defined as the region in between the lower and upper approximation. By introducing this boundary region, where compounds may possibly belong to a class, we introduce uncertainty into the analysis.
Mentions: We define two further parameters: the lower approximation and the upper approximation where X is a subset of U. Effectively, we can consider this as defining the range of descriptor values where every entry belongs to a specific class/category and the range which contains all the values of a class/category. In this way, every entry within the lower approximation material belongs to the same class, while in the upper approximation, all materials of a class are contained, while at the same time materials of other classes may also be present. In a situation where all compounds of a class were clustered together in the attribute space, the lower and upper approximations would be equal. The definition of the boundary region for low LY compounds within B = (density, EC factor) for very high LY compounds is provided in figure 3.

View Article: PubMed Central - PubMed

ABSTRACT

In this review, we provide an overview of the development of quantitative structure–property relationships incorporating the impact of data uncertainty from small, limited knowledge data sets from which we rapidly develop new and larger databases. Unlike traditional database development, this informatics based approach is concurrent with the identification and discovery of the key metrics controlling structure–property relationships; and even more importantly we are now in a position to build materials databases based on design ‘intent’ and not just design parameters. This permits for example to establish materials databases that can be used for targeted multifunctional properties and not just one characteristic at a time as is presently done. This review provides a summary of the computational logic of building such virtual databases and gives some examples in the field of complex inorganic solids for scintillator applications.

No MeSH data available.