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Configurational Isomerism in Bimetallic Decametalates.

Aleksandar Kondinski
Published in: Materials (Basel, Switzerland) (2024)
In this work, we report on the development of a computational algorithm that explores the configurational isomer space of bimetallic decametalates with general formula MxM10-x'O28q. For x being a natural number in the range of 0 to 10, the algorithm identifies 318 unique configurational isomers. The algorithm is used to generate mixed molybdenum(VI)-vanadium(V) systems MoxV10-xO288- for x=0,1,2, and 3 that are of experimental relevance. The application of the density functional theory (DFT) effectively predicts stability trends that correspond well with empirical observations. In dimolybdenum-substituted decavanadate systems, we discover that a two-electron reduction preferentially stabilizes a configurational isomer due to the formation of metal-metal bonding. The particular polyoxometalate structure is of interest for further experimental studies.
Keyphrases
  • density functional theory
  • machine learning
  • deep learning
  • molecular dynamics
  • metal organic framework
  • molecular docking
  • neural network
  • gene expression
  • crystal structure