Browsing Kjemisk institutt by Author "De Bin, Riccardo"

Now showing items 1-2 of 2

  • Deep learning metal complex properties with natural quantum graphs 
    Kneiding, Hannes; Lukin, Ruslan; Lang, Lucas; Reine, Simen; Pedersen, Thomas Bondo; De Bin, Riccardo; Balcells, David (Journal article / Tidsskriftartikkel / PublishedVersion; Peer reviewed, 2023)
    Machine learning can make a strong contribution to accelerating the discovery of transition metal complexes (TMC). These compounds will play a key role in the development of new technologies for which there is an urgent ...
  • Machine learning dihydrogen activation in the chemical space surrounding Vaska's complex 
    Friederich, Pascal; Dos Passos Gomes, Gabriel; De Bin, Riccardo; Aspuru-Guzik, Alán; Balcells, David (Journal article / Tidsskriftartikkel / PublishedVersion; Peer reviewed, 2020)
    Homogeneous catalysis using transition metal complexes is ubiquitously used for organic synthesis, as well as technologically relevant in applications such as water splitting and CO2 reduction. The key steps underlying ...