Database for Quasicrystals

 


Quasicrystals are materials with non-periodic symmetry. It separates them from conventional crystals.  Approximant crystal are precursor materials. They are closely related to quasicrystals. They share structural features, but retain atomic arrangements. 

These materials can  display unique physical properties. These features can be unique temperature, dependencies, and electrical and thermal conductivity. There is no comprehensive database and it is a huge barrier in machine learning. 

Development of the quasicrystal database Will stimulate the growth of new materials. The goal is within reach, and published in the journal Scientific Data.

Scientists developed the world first database for quasicrystals and their approximants. It’s called “HYPOD-X”. Hypermaterials open database for X. (This is where X represents a quirk for application targets, like machine learning)

HYPOD-X Has three data sets. They are composition, data set, the phase diagram, data set, and the property data set. The data is manually or semi automatically extracted. It is under review before added to the database.

Data quality is enhanced by using automated algorithms for Data extraction. The data volume is 10 times greater than the previous study of quasicrystals by closely reviewing the data, new patterns that were previously overlooked could be discovered!

HYPOD-X is a valuable new tool for quasicrystal research. 

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