Quantifying Chemical Structure and Atomic Energies in Amorphous Silicon Networks.

@inproceedings{Bernstein2018QuantifyingCS,
  title={Quantifying Chemical Structure and Atomic Energies in Amorphous Silicon Networks.},
  author={N. Bernstein and B. Bhattarai and G. Cs'anyi and D. Drabold and S. Elliott and V. Deringer},
  year={2018}
}
  • N. Bernstein, B. Bhattarai, +3 authors V. Deringer
  • Published 2018
  • Physics
  • Amorphous materials are coming within reach of realistic computer simulations, but new approaches are needed to fully understand their intricate atomic structures. Here, we show how machine-learning (ML)-based techniques can give new, quantitative chemical insight into the atomic-scale structure of amorphous silicon (a-Si). Based on a similarity function (“kernel”), we define a structural metric that unifies the description of nearestand nextnearest-neighbor environments in the amorphous state… CONTINUE READING

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    References

    Stukowski , Model . Simul
    • Mater . Sci . Eng .
    • 2004