Abstract

Estimating the coordination environment of non-crystalline metal complexes has been an important issue. In this study, we applied machine learning methods to extract features of coordination number and coordination elements from X-ray absorption near edge structure (XANES) spectra of 44 Ni complexes. The spectra were clearly classified according to the coordination number and coordination elements. The similarity between spectra was visualized as a 2D map by dimensionality reduction using multidimensional scaling (MDS).

Original languageEnglish
Pages (from-to)289-291
Number of pages3
JournalChemistry Letters
Volume52
Issue number4
DOIs
Publication statusPublished - 2023 Apr

Keywords

  • Machine learning
  • Structure estimation
  • XANES

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