First-Principles and Machine Learning Study of Anharmonic Vibration and Dielectric Properties of Materials

First-Principles and Machine Learning Study of Anharmonic Vibration and Dielectric Properties of Materials book cover

First-Principles and Machine Learning Study of Anharmonic Vibration and Dielectric Properties of Materials

Author(s): Tomohito Amano (Author)

  • Publisher: Springer
  • Publication Date: 31 May 2025
  • Language: English
  • Print length: 237 pages
  • ISBN-10: 9819640237
  • ISBN-13: 9789819640232

Book Description

The book presents the author's development of two first-principles methods to calculate dielectric properties of materials based on anharmonic phonon and machine learning, and demonstrates an in-depth analysis of anharmonic crystals and molecular liquids. The anharmonic phonon method, combined with Born effective charges, is useful to study dielectric properties of crystals. The recently developed self-consistent phonon theory (SCPH) enables accurate simulations in strongly anharmonic materials. The author reveals that the combination of SCPH with the four-phonon scattering term accurately reproduces experimental spectra, and discusses how anharmonic phonon self-energies affect the dielectric properties.

The second method is molecular dynamics with Wannier centers―the mass centers of Wannier functions. The author constructs a machine learning model that learns Wannier centers for each chemical bond from atomic coordinates to accurately predict the dipole moments. The developed method is, in principle, applicable to molecules of arbitrary size. Its effectiveness is demonstrated and the dielectric properties of several alcohols, including dipole moments, dielectric constants, and absorption spectra, are analyzed. This book benefits students and researchers interested in anharmonic phonons, machine learning, and dielectric properties.

Editorial Reviews

From the Back Cover

The book presents the author's development of two first-principles methods to calculate dielectric properties of materials based on anharmonic phonon and machine learning, and demonstrates an in-depth analysis of anharmonic crystals and molecular liquids. The anharmonic phonon method, combined with Born effective charges, is useful to study dielectric properties of crystals. The recently developed self-consistent phonon theory (SCPH) enables accurate simulations in strongly anharmonic materials. The author reveals that the combination of SCPH with the four-phonon scattering term accurately reproduces experimental spectra, and discusses how anharmonic phonon self-energies affect the dielectric properties.

The second method is molecular dynamics with Wannier centers—the mass centers of Wannier functions. The author constructs a machine learning model that learns Wannier centers for each chemical bond from atomic coordinates to accurately predict the dipole moments. The developed method is, in principle, applicable to molecules of arbitrary size. Its effectiveness is demonstrated and the dielectric properties of several alcohols, including dipole moments, dielectric constants, and absorption spectra, are analyzed. This book benefits students and researchers interested in anharmonic phonons, machine learning, and dielectric properties.

About the Author

Tomohito Amano is a theoretical physicist in condensed matter physics at the University of Tokyo. After his Bachelor of Science program at the University of Tokyo, he started his graduate research in the group led by Professor Shinji Tsuneyuki in 2019, and received his Ph.D. from the Department of Physics, the School of Science, the University of Tokyo in 2024. He was awarded the School of Science Encouragement Award AY2023 in 2024. His research interest lies in density functional theory, anharmonic phonon theory, molecular dynamics, machine learning, and dielectric property of materials.

View on Amazon

未经允许不得转载:电子书百科大全 » First-Principles and Machine Learning Study of Anharmonic Vibration and Dielectric Properties of Materials

评论 抢沙发

评论前必须登录!

立即登录   注册