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50 та иш

Иш: Neural network and experimental thermodynamics study of YCrO3-δ for efficient solar thermochemical hydrogen production

  1. Learning representations by back-propagating errors

    David E. Rumelhart, Geoffrey E. Hinton, Ronald J. Williams

    Мақола198615 иқтибос
    ABI
  2. Machine learning for molecular and materials science

    Keith T. Butler, Daniel W. Davies, Hugh Cartwright +2

    Шарҳ мақола20184 иқтибос
    ABI
  3. Concentrating solar thermal power and thermochemical fuels

    Manuel Romero, Aldo Steinfeld

    Мақола20123 иқтибос
    ABI
  4. Research opportunities to advance solar energy utilization

    Nathan S. Lewis

    Шарҳ мақола20163 иқтибос
    ABI
  5. Overview of Artificial Neural Networks

    Jinming Zou, Yi Han, Sung‐Sau So

    Шарҳ мақола20082 иқтибос
    ABI
  6. Сарлавҳасиз

    Бошқа2 иқтибос
    ABI
  7. Oxygen exchange materials for solar thermochemical splitting of H2O and CO2: a review

    Jonathan R. Scheffe, Aldo Steinfeld

    Шарҳ мақола20142 иқтибос
    ABI
  8. Materials design of perovskite solid solutions for thermochemical applications

    Josua Vieten, Brendan Bulfin, Patrick Huck +7

    Мақола20192 иқтибос
    ABI