Investigation of Au(111)/Li<sub>3</sub>PO<sub>4</sub> Interface Structures using Neural Network Potential
POSTER
Abstract
Recently, the construction of interatomic potentials using first-principles calculation data and machine-learning technique has been widely tried because of higher reliability and low computational costs. In the present study, we have tried to construct the four-element neural network potential (NNP) [1,2] to investigate the Au(111)/Li3PO4 interface system, where the understanding of the interface structures and Li-ion distribution near the interface is of significance for the development of all-solid state Li-ion batteries and novel memory devices [3]. Using the constructed NNP, we then performed structure optimization with a large interface model of Au(111)/Li3PO4. In the meeting, we will discuss the calculated interface structures and the Li defect formation energies.
[1] J. Behler et al., Phys. Rev. Lett. 98, 146401 (2007).
[2] W. Li et al., J. Chem. Phys. 147, 214106 (2017).
[3] I. Sugiyama et al., APL Mater. 5, 046105 (2017).
[1] J. Behler et al., Phys. Rev. Lett. 98, 146401 (2007).
[2] W. Li et al., J. Chem. Phys. 147, 214106 (2017).
[3] I. Sugiyama et al., APL Mater. 5, 046105 (2017).
Presenters
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Koji Shimizu
The University of Tokyo, Department of Materials Engineering, The University of Tokyo
Authors
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Koji Shimizu
The University of Tokyo, Department of Materials Engineering, The University of Tokyo
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Wei Liu
Department of Materials Engineering, The University of Tokyo
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Wenwen Li
AIST, National Institute of Advanced Industrial Science and Technology
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Yasunobu Ando
CD-FMat, AIST, AIST, National Institute of Advanced Industrial Science and Technology
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Emi Minamitani
Institute for Molecular Science
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Satoshi Watanabe
The University of Tokyo, Department of Materials Engineering, The University of Tokyo