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 language | English |
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Pages (from-to) | 289-291 |
Number of pages | 3 |
Journal | Chemistry Letters |
Volume | 52 |
Issue number | 4 |
DOIs | |
Publication status | Published - 2023 Apr |
Keywords
- Machine learning
- Structure estimation
- XANES