Novel machine learning-based cluster analysis method that leverages target material property

Conventional clustering techniques often focus on basic features like crystal structure and elemental composition, neglecting target properties such as band gaps and dielectric constants. A new study introduced a machine learning-powered clustering model that incorporates both basic features and target properties, successfully grouping over 1,000 inorganic materials. This model provides insights into material relationships, potential applications, and identifies key factors to balance band gaps and dielectric constants, addressing their trade-off relationship.

from Top Technology News -- ScienceDaily https://ift.tt/kpILzPM