• Corpus ID: 51793117

Machine Learning of Energetic Material Properties

@article{Barnes2018MachineLO,
  title={Machine Learning of Energetic Material Properties},
  author={Brian C. Barnes and Daniel C. Elton and Zois Boukouvalas and DeCarlos E. Taylor and William D. Mattson and Mark D. Fuge and Peter W. Chung},
  journal={arXiv: Materials Science},
  year={2018}
}
In this work, we discuss use of machine learning techniques for rapid prediction of detonation properties including explosive energy, detonation velocity, and detonation pressure. Further, analysis is applied to individual molecules in order to explore the contribution of bonding motifs to these properties. Feature descriptors evaluated include Morgan fingerprints, E-state vectors, a custom "sum over bonds" descriptor, and coulomb matrices. Algorithms discussed include kernel ridge regression… 

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