LEADER 04300nam 22007575 450 001 9911007485503321 005 20251006111625.0 010 $a981-9640-24-5 024 7 $a10.1007/978-981-96-4024-9 035 $a(CKB)39124462600041 035 $a(DE-He213)978-981-96-4024-9 035 $a(MiAaPQ)EBC32142510 035 $a(Au-PeEL)EBL32142510 035 $a(EXLCZ)9939124462600041 100 $a20250531d2025 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aFirst-Principles and Machine Learning Study of Anharmonic Vibration and Dielectric Properties of Materials /$fby Tomohito Amano 205 $a1st ed. 2025. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2025. 215 $a1 online resource (XVIII, 219 p. 52 illus., 45 illus. in color.) 225 1 $aSpringer Theses, Recognizing Outstanding Ph.D. Research,$x2190-5061 311 08$a981-9640-23-7 327 $aChapter 1 Introduction -- Chapter 2 Density Functional Theory -- Chapter 3 Anharmonic Phonon Theory -- Chapter 4 Modern Theory and Machine Learning of Polarization -- Chapter 5 Dielectric Properties of Strongly Anharmonic TiO2 -- Chapter 6 Dielectric Properties of Liquid Alcohols and Its Polymers -- Chapter 7 Conclusion. 330 $aThe book presents the author's development of two first-principles methods to calculate dielectric properties of materials based on anharmonic phonon and machine learning, and demonstrates an in-depth analysis of anharmonic crystals and molecular liquids. The anharmonic phonon method, combined with Born effective charges, is useful to study dielectric properties of crystals. The recently developed self-consistent phonon theory (SCPH) enables accurate simulations in strongly anharmonic materials. The author reveals that the combination of SCPH with the four-phonon scattering term accurately reproduces experimental spectra, and discusses how anharmonic phonon self-energies affect the dielectric properties. The second method is molecular dynamics with Wannier centers?the mass centers of Wannier functions. The author constructs a machine learning model that learns Wannier centers for each chemical bond from atomic coordinates to accurately predict the dipole moments. The developed method is, in principle, applicable to molecules of arbitrary size. Its effectiveness is demonstrated and the dielectric properties of several alcohols, including dipole moments, dielectric constants, and absorption spectra, are analyzed. This book benefits students and researchers interested in anharmonic phonons, machine learning, and dielectric properties. 410 0$aSpringer Theses, Recognizing Outstanding Ph.D. Research,$x2190-5061 606 $aMathematical physics 606 $aComputer simulation 606 $aMachine learning 606 $aSemiconductors 606 $aCondensed matter 606 $aMaterials science$xData processing 606 $aElectronic structure 606 $aQuantum chemistry$xComputer programs 606 $aComputational Physics and Simulations 606 $aMachine Learning 606 $aSemiconductors 606 $aCondensed Matter Physics 606 $aCondensed Matter 606 $aElectronic Structure Calculations 615 0$aMathematical physics. 615 0$aComputer simulation. 615 0$aMachine learning. 615 0$aSemiconductors. 615 0$aCondensed matter. 615 0$aMaterials science$xData processing. 615 0$aElectronic structure. 615 0$aQuantum chemistry$xComputer programs. 615 14$aComputational Physics and Simulations. 615 24$aMachine Learning. 615 24$aSemiconductors. 615 24$aCondensed Matter Physics. 615 24$aCondensed Matter. 615 24$aElectronic Structure Calculations. 676 $a530.10285 700 $aAmano$b Tomohito$4aut$4http://id.loc.gov/vocabulary/relators/aut$01821887 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911007485503321 996 $aFirst-Principles and Machine Learning Study of Anharmonic Vibration and Dielectric Properties of Materials$94387820 997 $aUNINA