Published August 3, 2020 | Version v1
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Effects of the density and composition on the properties of amorphous alumina: a high dimensional neural network potential study

  • 1. Research Center for Computational Design of Advanced Functional Materials, National Institute of Advanced Industrial Science and Technology, Tsukuba, Ibaraki 305-8568, Japan
  • 2. Department of Materials Engineering, The University of Tokyo, Bunkyo, Tokyo 113-8656, Japan
  • 3. Center for Materials Research by Information Integration, Research and Services Division of Materials Data and Integrated System, National Institute for Materials Science, Tsukuba, Ibaraki 305-0047, Japan

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Description

Amorphous alumina (a-AlOx), which plays important roles in several technological fields, shows wide variation of the density and composition. However, their influences on the properties of a-AlOx have rarely been investigated from a theoretical perspective. In this study, high dimensional neural network (NN) potentials were constructed to generate a series of atomic structures of a-AlOx with different densities (2.6–3.3 g/cm3) and O/Al ratios (1.0–1.75). The structural, vibrational, mechanical, and thermal properties of the a-AlOx models were investigated, as well as the Li and Cu diffusion behaviour in the models. The results showed that the density and composition had different degrees of effects on the different properties. The structural and vibrational properties were strongly affected by the composition, whereas the mechanical properties were mainly determined by the density. The thermal conductivity was affected by both the density and composition of a-AlOx. However, the effects on the Li and Cu diffusion behaviour were relatively unclear.

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References

Journal reference
W. Li, Y. Ando, S. Watanate, Journal of Chemical Physics 153, 164119 (2020), doi: 10.1063/5.0026289

Journal reference
W. Li, Y. Ando, S. Watanate, Journal of Chemical Physics 153, 164119 (2020)