Density-of-states similarity descriptor for unsupervised learning from materials data

HIGHLIGHTS

• who: Martin Kuban from the (UNIVERSITY) have published the article: Density-of-states similarity descriptor for unsupervised learning from materials data, in the Journal: (JOURNAL)
• what: The authors aim at obtaining deeper understanding of large materials data spaces by rationalizing the reasons behind features that materials may share. The authors demonstrate the approach by the similarity of materials in terms of their electronic properties. To this extent the authors develop a tunable DOS fingerprint that encodes the DOS of a material into a binary-valued two-dimensional (2D) map, stimulated by the work of Ref . . .
  

   

  

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