Deep learning of accurate force field of ferroelectric HfO2

Wu, Jing; Zhang, Yuzhi; Zhang, Linfeng; Liu, Shi

doi:10.1103/physrevb.103.024108

Deep learning of accurate force field of ferroelectric HfO 2

Journal Article · Fri Jan 29 00:00:00 EST 2021 · Physical Review. B

DOI:https://doi.org/10.1103/physrevb.103.024108· OSTI ID:1853191

^[1]; Zhang, Yuzhi ^[2]; Zhang, Linfeng ^[3]; ^[4]

Fudan Univ., Shanghai (China); Westlake Univ., Zhejiang (China); Westlake Inst. for Advanced Study, Zhejiang (China); OSTI
Peking Univ., Beijing (China)
Princeton Univ., NJ (United States)
Westlake Univ., Zhejiang (China); Westlake Inst. for Advanced Study, Zhejiang (China); Key Lab. for Quantum Materials of Zhejiang Province, Zhejiang (China)

The discovery of ferroelectricity in HfO₂-based thin films opens up new opportunities for using this silicon-compatible ferroelectric to realize low-power logic circuits and high-density nonvolatile memories. The functional performances of ferroelectrics are intimately related to their dynamic responses to external stimuli such as electric fields at finite temperatures. Molecular dynamics is an ideal technique for investigating dynamical processes on large length and time scales, though its applications to new materials are often hindered by the limited availability and accuracy of classical force fields. Here we present a deep neural network–based interatomic force field of HfO₂ learned from ab initio data using a concurrent learning procedure. The model potential is able to predict structural properties such as elastic constants, equation of states, phonon dispersion relationships, and phase transition barriers of various hafnia polymorphs with accuracy comparable with density functional theory calculations. Here, the validity of this model potential is further confirmed by the reproduction of experimental sequences of temperature-driven ferroelectric-paraelectric phase transitions of HfO₂ with isobaric-isothermal ensemble molecular dynamics simulations. We suggest a general approach to extend the model potential of HfO₂ to related material systems including dopants and defects.

View Accepted Manuscript (DOE)

Research Organization:: Princeton Univ., NJ (United States)

Sponsoring Organization:: National Natural Science Foundation of China; USDOE Office of Science (SC); Westlake Education Foundation

Grant/Contract Number:: SC0019394

OSTI ID:: 1853191

Journal Information:: Physical Review. B, Journal Name: Physical Review. B Journal Issue: 2 Vol. 103; ISSN 2469-9950

Publisher:: American Physical Society (APS)Copyright Statement

Country of Publication:: United States

Language:: English

References (90)

Ferroelectricity and Antiferroelectricity of Doped Thin HfO ₂ -Based Films Park, Min Hyuk; Lee, Young Hwan; Kim, Han Joon Advanced Materials, Vol. 27, Issue 11 https://doi.org/10.1002/adma.201404531	journal	February 2015
Origin of Temperature-Dependent Ferroelectricity in Si-Doped HfO ₂ Park, Min Hyuk; Chung, Ching-Chang; Schenk, Tony Advanced Electronic Materials, Vol. 4, Issue 4 https://doi.org/10.1002/aelm.201700489	journal	March 2018
A High-Speed and Low-Power Multistate Memory Based on Multiferroic Tunnel Junctions Huang, Weichuan; Zhao, Wenbo; Luo, Zhen Advanced Electronic Materials, Vol. 4, Issue 4 https://doi.org/10.1002/aelm.201700560	journal	March 2018
Thermodynamic and Kinetic Origins of Ferroelectricity in Fluorite Structure Oxides Park, Min Hyuk; Lee, Young Hwan; Mikolajick, Thomas Advanced Electronic Materials, Vol. 5, Issue 3 https://doi.org/10.1002/aelm.201800522	journal	December 2018
Pressure-induced phase transitions in silicon studied by neural network-based metadynamics simulations Behler, Jörg; Martoňák, Roman; Donadio, Davide physica status solidi (b), Vol. 245, Issue 12 https://doi.org/10.1002/pssb.200844219	journal	December 2008
Fast Parallel Algorithms for Short-Range Molecular Dynamics Plimpton, Steve Journal of Computational Physics, Vol. 117, Issue 1 https://doi.org/10.1006/jcph.1995.1039	journal	March 1995
A computational study of hafnia-based ferroelectric memories: from ab initio via physical modeling to circuit models of ferroelectric device Pešić, Milan; Künneth, Christopher; Hoffmann, Michael Journal of Computational Electronics, Vol. 16, Issue 4 https://doi.org/10.1007/s10825-017-1053-0	journal	August 2017
Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set Kresse, G.; Furthmüller, J. Computational Materials Science, Vol. 6, Issue 1, p. 15-50 https://doi.org/10.1016/0927-0256(96)00008-0	journal	July 1996
New developments in evolutionary structure prediction algorithm USPEX Lyakhov, Andriy O.; Oganov, Artem R.; Stokes, Harold T. Computer Physics Communications, Vol. 184, Issue 4 https://doi.org/10.1016/j.cpc.2012.12.009	journal	April 2013
DeePMD-kit: A deep learning package for many-body potential energy representation and molecular dynamics Wang, Han; Zhang, Linfeng; Han, Jiequn Computer Physics Communications, Vol. 228 https://doi.org/10.1016/j.cpc.2018.03.016	journal	July 2018
DP-GEN: A concurrent learning platform for the generation of reliable deep learning based potential energy models Zhang, Yuzhi; Wang, Haidi; Chen, Weijie Computer Physics Communications https://doi.org/10.1016/j.cpc.2020.107206	journal	February 2020
Theoretical prediction on thermal and mechanical properties of high entropy (Zr0.2Hf0.2Ti0.2Nb0.2Ta0.2)C by deep learning potential Dai, Fu-Zhi; Wen, Bo; Sun, Yinjie Journal of Materials Science & Technology, Vol. 43 https://doi.org/10.1016/j.jmst.2020.01.005	journal	April 2020
Ferroelectric phase transitions in nanoscale HfO 2 films enable giant pyroelectric energy conversion and highly efficient supercapacitors Hoffmann, Michael; Schroeder, Uwe; Künneth, Christopher Nano Energy, Vol. 18 https://doi.org/10.1016/j.nanoen.2015.10.005	journal	November 2015
First principles phonon calculations in materials science Togo, Atsushi; Tanaka, Isao Scripta Materialia, Vol. 108 https://doi.org/10.1016/j.scriptamat.2015.07.021	journal	November 2015
Dopants Promoting Ferroelectricity in Hafnia: Insights from a comprehensive Chemical Space Exploration Batra, Rohit; Huan, Tran Doan; Rossetti, George A. Chemistry of Materials, Vol. 29, Issue 21 https://doi.org/10.1021/acs.chemmater.7b02835	journal	October 2017
Factors Favoring Ferroelectricity in Hafnia: A First-Principles Computational Study Batra, Rohit; Huan, Tran Doan; Jones, Jacob L. The Journal of Physical Chemistry C, Vol. 121, Issue 8 https://doi.org/10.1021/acs.jpcc.6b11972	journal	February 2017
Origin of the Intrinsic Ferroelectricity of HfO ₂ from ab Initio Molecular Dynamics Fan, P.; Zhang, Y. K.; Yang, Q. The Journal of Physical Chemistry C, Vol. 123, Issue 35 https://doi.org/10.1021/acs.jpcc.9b04106	journal	August 2019
How Evolutionary Crystal Structure Prediction Works—and Why Oganov, Artem R.; Lyakhov, Andriy O.; Valle, Mario Accounts of Chemical Research, Vol. 44, Issue 3 https://doi.org/10.1021/ar1001318	journal	March 2011
Origin of ferroelectricity in perovskite oxides Cohen, Ronald E. Nature, Vol. 358, Issue 6382 https://doi.org/10.1038/358136a0	journal	July 1992
Intrinsic ferroelectric switching from first principles Liu, Shi; Grinberg, Ilya; Rappe, Andrew M. Nature, Vol. 534, Issue 7607 https://doi.org/10.1038/nature18286	journal	June 2016
A highly CMOS compatible hafnia-based ferroelectric diode Luo, Qing; Cheng, Yan; Yang, Jianguo Nature Communications, Vol. 11, Issue 1 https://doi.org/10.1038/s41467-020-15159-2	journal	March 2020
Complex reaction processes in combustion unraveled by neural network-based molecular dynamics simulation Zeng, Jinzhe; Cao, Liqun; Xu, Mingyuan Nature Communications, Vol. 11, Issue 1 https://doi.org/10.1038/s41467-020-19497-z	journal	November 2020
Machine-learned interatomic potentials by active learning: amorphous and liquid hafnium dioxide Sivaraman, Ganesh; Krishnamoorthy, Anand Narayanan; Baur, Matthias npj Computational Materials, Vol. 6, Issue 1 https://doi.org/10.1038/s41524-020-00367-7	journal	July 2020
Unveiling the double-well energy landscape in a ferroelectric layer Hoffmann, Michael; Fengler, Franz P. G.; Herzig, Melanie Nature, Vol. 565, Issue 7740 https://doi.org/10.1038/s41586-018-0854-z	journal	January 2019
Enhanced ferroelectricity in ultrathin films grown directly on silicon Cheema, Suraj S.; Kwon, Daewoong; Shanker, Nirmaan Nature, Vol. 580, Issue 7804 https://doi.org/10.1038/s41586-020-2208-x	journal	April 2020
ANI-1: an extensible neural network potential with DFT accuracy at force field computational cost Smith, J. S.; Isayev, O.; Roitberg, A. E. Chemical Science, Vol. 8, Issue 4 https://doi.org/10.1039/C6SC05720A	journal	January 2017
An extensive study of the influence of dopants on the ferroelectric properties of HfO ₂ Starschich, S.; Boettger, U. Journal of Materials Chemistry C, Vol. 5, Issue 2 https://doi.org/10.1039/C6TC04807B	journal	January 2017
Surface and grain boundary energy as the key enabler of ferroelectricity in nanoscale hafnia-zirconia: a comparison of model and experiment Park, Min Hyuk; Lee, Young Hwan; Kim, Han Joon Nanoscale, Vol. 9, Issue 28 https://doi.org/10.1039/C7NR02121F	journal	January 2017
Understanding the formation of the metastable ferroelectric phase in hafnia–zirconia solid solution thin films Park, Min Hyuk; Lee, Young Hwan; Kim, Han Joon Nanoscale, Vol. 10, Issue 2 https://doi.org/10.1039/C7NR06342C	journal	January 2018
A comprehensive study on the structural evolution of HfO ₂ thin films doped with various dopants Park, M. H.; Schenk, T.; Fancher, C. M. Journal of Materials Chemistry C, Vol. 5, Issue 19 https://doi.org/10.1039/C7TC01200D	journal	January 2017
Understanding the influence of defects and surface chemistry on ferroelectric switching: a ReaxFF investigation of BaTiO ₃ Akbarian, Dooman; Yilmaz, Dundar E.; Cao, Ye Physical Chemistry Chemical Physics, Vol. 21, Issue 33 https://doi.org/10.1039/C9CP02955A	journal	January 2019
Free energy of proton transfer at the water–TiO ₂ interface from ab initio deep potential molecular dynamics Calegari Andrade, Marcos F.; Ko, Hsin-Yu; Zhang, Linfeng Chemical Science, Vol. 11, Issue 9 https://doi.org/10.1039/C9SC05116C	journal	January 2020
Crystal structure prediction using ab initio evolutionary techniques: Principles and applications Oganov, Artem R.; Glass, Colin W. The Journal of Chemical Physics, Vol. 124, Issue 24 https://doi.org/10.1063/1.2210932	journal	June 2006
Using neural networks, optimized coordinates, and high-dimensional model representations to obtain a vinyl bromide potential surface Manzhos, Sergei; Carrington, Tucker The Journal of Chemical Physics, Vol. 129, Issue 22 https://doi.org/10.1063/1.3021471	journal	December 2008
Ferroelectricity in hafnium oxide thin films Böscke, T. S.; Müller, J.; Bräuhaus, D. Applied Physics Letters, Vol. 99, Issue 10 https://doi.org/10.1063/1.3634052	journal	September 2011
The origin of ferroelectricity in Hf _1−x Zr _x O ₂ : A computational investigation and a surface energy model Materlik, R.; Künneth, C.; Kersch, A. Journal of Applied Physics, Vol. 117, Issue 13 https://doi.org/10.1063/1.4916707	journal	April 2015
On the structural origins of ferroelectricity in HfO ₂ thin films Sang, Xiahan; Grimley, Everett D.; Schenk, Tony Applied Physics Letters, Vol. 106, Issue 16 https://doi.org/10.1063/1.4919135	journal	April 2015
Ferroelectricity in undoped hafnium oxide Polakowski, Patrick; Müller, Johannes Applied Physics Letters, Vol. 106, Issue 23 https://doi.org/10.1063/1.4922272	journal	June 2015
Stabilization of metastable phases in hafnia owing to surface energy effects Batra, Rohit; Tran, Huan Doan; Ramprasad, Rampi Applied Physics Letters, Vol. 108, Issue 17 https://doi.org/10.1063/1.4947490	journal	April 2016
Impact of mechanical stress on ferroelectricity in (Hf _0.5 Zr _0.5 )O ₂ thin films Shiraishi, Takahisa; Katayama, Kiliha; Yokouchi, Tatsuhiko Applied Physics Letters, Vol. 108, Issue 26 https://doi.org/10.1063/1.4954942	journal	June 2016
Enhancing ferroelectricity in dopant-free hafnium oxide Pal, Ashish; Narasimhan, Vijay Kris; Weeks, Stephen Applied Physics Letters, Vol. 110, Issue 2 https://doi.org/10.1063/1.4973928	journal	January 2017
Ion migration in crystalline and amorphous HfO _X Schie, Marcel; Müller, Michael P.; Salinga, Martin The Journal of Chemical Physics, Vol. 146, Issue 9 https://doi.org/10.1063/1.4977453	journal	March 2017
Modeling ferroelectric film properties and size effects from tetragonal interlayer in Hf _1– _x Zr _x O ₂ grains Künneth, Christopher; Materlik, Robin; Kersch, Alfred Journal of Applied Physics, Vol. 121, Issue 20 https://doi.org/10.1063/1.4983811	journal	May 2017
Kinetic pathway of the ferroelectric phase formation in doped HfO ₂ films Xu, Lun; Nishimura, Tomonori; Shibayama, Shigehisa Journal of Applied Physics, Vol. 122, Issue 12 https://doi.org/10.1063/1.5003918	journal	September 2017
Nucleation limited switching (NLS) model for HfO ₂ -based metal-ferroelectric-metal (MFM) capacitors: Switching kinetics and retention characteristics Gong, N.; Sun, X.; Jiang, H. Applied Physics Letters, Vol. 112, Issue 26 https://doi.org/10.1063/1.5010207	journal	June 2018
Optimization and validation of a deep learning CuZr atomistic potential: Robust applications for crystalline and amorphous phases with near-DFT accuracy Andolina, Christopher M.; Williamson, Philip; Saidi, Wissam A. The Journal of Chemical Physics, Vol. 152, Issue 15 https://doi.org/10.1063/5.0005347	journal	April 2020
How van der Waals interactions determine the unique properties of water Morawietz, Tobias; Singraber, Andreas; Dellago, Christoph Proceedings of the National Academy of Sciences, Vol. 113, Issue 30 https://doi.org/10.1073/pnas.1602375113	journal	July 2016
Ferroelectronic ram memory family for critical data storage Bondurant, David Ferroelectrics, Vol. 112, Issue 1 https://doi.org/10.1080/00150199008008233	journal	December 1990
Isotope effects in liquid water via deep potential molecular dynamics Ko, Hsin-Yu; Zhang, Linfeng; Santra, Biswajit Molecular Physics, Vol. 117, Issue 22 https://doi.org/10.1080/00268976.2019.1652366	journal	October 2019
Silicon potentials investigated using density functional theory fitted neural networks Sanville, E.; Bholoa, A.; Smith, R. Journal of Physics: Condensed Matter, Vol. 20, Issue 28 https://doi.org/10.1088/0953-8984/20/28/285219	journal	June 2008
Development of a bond-valence based interatomic potential for BiFeO ₃ for accurate molecular dynamics simulations Liu, Shi; Grinberg, Ilya; Rappe, Andrew M. Journal of Physics: Condensed Matter, Vol. 25, Issue 10 https://doi.org/10.1088/0953-8984/25/10/102202	journal	February 2013
Molecular dynamics simulation of amorphous HfO ₂ for resistive RAM applications Broglia, G.; Ori, G.; Larcher, L. Modelling and Simulation in Materials Science and Engineering, Vol. 22, Issue 6 https://doi.org/10.1088/0965-0393/22/6/065006	journal	July 2014
Real-time studies of ferroelectric domain switching: a review Li, Linze; Xie, Lin; Pan, Xiaoqing Reports on Progress in Physics, Vol. 82, Issue 12 https://doi.org/10.1088/1361-6633/ab28de	journal	November 2019
Origin of Pyroelectricity in Ferroelectric HfO ₂ Liu, J.; Liu, S.; Liu, L. H. Physical Review Applied, Vol. 12, Issue 3 https://doi.org/10.1103/PhysRevApplied.12.034032	journal	September 2019
Machine learning the density functional theory potential energy surface for the inorganic halide perovskite CsPbBr 3 Thomas, John C.; Bechtel, Jonathon S.; Natarajan, Anirudh Raju Physical Review B, Vol. 100, Issue 13 https://doi.org/10.1103/PhysRevB.100.134101	journal	October 2019
Projector augmented-wave method Blöchl, P. E. Physical Review B, Vol. 50, Issue 24, p. 17953-17979 https://doi.org/10.1103/PhysRevB.50.17953	journal	December 1994
Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set Kresse, G.; Furthmüller, J. Physical Review B, Vol. 54, Issue 16, p. 11169-11186 https://doi.org/10.1103/PhysRevB.54.11169	journal	October 1996
From ultrasoft pseudopotentials to the projector augmented-wave method Kresse, G.; Joubert, D. Physical Review B, Vol. 59, Issue 3, p. 1758-1775 https://doi.org/10.1103/PhysRevB.59.1758	journal	January 1999
Phase Transition, Stability, and Depolarization Field in Ferroelectric Thin Films Batra, I. P.; Wurfel, P.; Silverman, B. D. Physical Review B, Vol. 8, Issue 7 https://doi.org/10.1103/PhysRevB.8.3257	journal	October 1973
Depolarization-Field-Induced Instability in Thin Ferroelectric Films—Experiment and Theory Wurfel, P.; Batra, I. P. Physical Review B, Vol. 8, Issue 11 https://doi.org/10.1103/PhysRevB.8.5126	journal	December 1973
Charge-optimized many-body potential for the hafnium/hafnium oxide system Shan, Tzu-Ray; Devine, Bryce D.; Kemper, Travis W. Physical Review B, Vol. 81, Issue 12 https://doi.org/10.1103/PhysRevB.81.125328	journal	March 2010
Ab initio quality neural-network potential for sodium Eshet, Hagai; Khaliullin, Rustam Z.; Kühne, Thomas D. Physical Review B, Vol. 81, Issue 18 https://doi.org/10.1103/PhysRevB.81.184107	journal	May 2010
Neural network interatomic potential for the phase change material GeTe Sosso, Gabriele C.; Miceli, Giacomo; Caravati, Sebastiano Physical Review B, Vol. 85, Issue 17 https://doi.org/10.1103/PhysRevB.85.174103	journal	May 2012
On representing chemical environments Bartók, Albert P.; Kondor, Risi; Csányi, Gábor Physical Review B, Vol. 87, Issue 18 https://doi.org/10.1103/PhysRevB.87.184115	journal	May 2013
Machine-learning approach for one- and two-body corrections to density functional theory: Applications to molecular and condensed water Bartók, Albert P.; Gillan, Michael J.; Manby, Frederick R. Physical Review B, Vol. 88, Issue 5 https://doi.org/10.1103/PhysRevB.88.054104	journal	August 2013
Reinterpretation of the bond-valence model with bond-order formalism: An improved bond-valence-based interatomic potential for PbTiO 3 Liu, Shi; Grinberg, Ilya; Takenaka, Hiroyuki Physical Review B, Vol. 88, Issue 10 https://doi.org/10.1103/PhysRevB.88.104102	journal	September 2013
Pathways towards ferroelectricity in hafnia Huan, Tran Doan; Sharma, Vinit; Rossetti, George A. Physical Review B, Vol. 90, Issue 6 https://doi.org/10.1103/PhysRevB.90.064111	journal	August 2014
Antiferroelectricity in thin-film ZrO 2 from first principles Reyes-Lillo, Sebastian E.; Garrity, Kevin F.; Rabe, Karin M. Physical Review B, Vol. 90, Issue 14 https://doi.org/10.1103/PhysRevB.90.140103	journal	October 2014
Learning scheme to predict atomic forces and accelerate materials simulations Botu, V.; Ramprasad, R. Physical Review B, Vol. 92, Issue 9 https://doi.org/10.1103/PhysRevB.92.094306	journal	September 2015
Deep Potential Molecular Dynamics: A Scalable Model with the Accuracy of Quantum Mechanics Zhang, Linfeng; Han, Jiequn; Wang, Han Physical Review Letters, Vol. 120, Issue 14 https://doi.org/10.1103/PhysRevLett.120.143001	journal	April 2018
Generalized Gradient Approximation Made Simple Perdew, John P.; Burke, Kieron; Ernzerhof, Matthias Physical Review Letters, Vol. 77, Issue 18, p. 3865-3868 https://doi.org/10.1103/PhysRevLett.77.3865	journal	October 1996
Generalized Neural-Network Representation of High-Dimensional Potential-Energy Surfaces Behler, Jörg; Parrinello, Michele Physical Review Letters, Vol. 98, Issue 14 https://doi.org/10.1103/PhysRevLett.98.146401	journal	April 2007
Active learning of uniformly accurate interatomic potentials for materials simulation Zhang, Linfeng; Lin, De-Ye; Wang, Han Physical Review Materials, Vol. 3, Issue 2 https://doi.org/10.1103/PhysRevMaterials.3.023804	journal	February 2019
Effects of growth orientations and epitaxial strains on phase stability of HfO 2 thin films Liu, Shi; Hanrahan, Brendan M. Physical Review Materials, Vol. 3, Issue 5 https://doi.org/10.1103/PhysRevMaterials.3.054404	journal	May 2019
Machine-learning-based interatomic potential for phonon transport in perfect crystalline Si and crystalline Si with vacancies Babaei, Hasan; Guo, Ruiqiang; Hashemi, Amirreza Physical Review Materials, Vol. 3, Issue 7 https://doi.org/10.1103/PhysRevMaterials.3.074603	journal	July 2019
Thickness and strain dependence of piezoelectric coefficient in BaTiO 3 thin films Kelley, K. P.; Yilmaz, D. E.; Collins, L. Physical Review Materials, Vol. 4, Issue 2 https://doi.org/10.1103/PhysRevMaterials.4.024407	journal	February 2020
Machine Learning a General-Purpose Interatomic Potential for Silicon Bartók, Albert P.; Kermode, James; Bernstein, Noam Physical Review X, Vol. 8, Issue 4 https://doi.org/10.1103/PhysRevX.8.041048	journal	December 2018
A 64-Mb Embedded FRAM Utilizing a 130-nm 5LM Cu/FSG Logic Process McAdams, H. P.; Acklin, R.; Blake, T. IEEE Journal of Solid-State Circuits, Vol. 39, Issue 4 https://doi.org/10.1109/JSSC.2004.825241	journal	April 2004
Why is nonvolatile ferroelectric memory field-effect transistor still elusive? Ma, T. P. IEEE Electron Device Letters, Vol. 23, Issue 7 https://doi.org/10.1109/LED.2002.1015207	journal	July 2002
The Past, the Present, and the Future of Ferroelectric Memories Mikolajick, T.; Schroeder, U.; Slesazeck, S. IEEE Transactions on Electron Devices, Vol. 67, Issue 4 https://doi.org/10.1109/TED.2020.2976148	journal	April 2020
Phase Relations and Volume Changes of Hafnia under High Pressure and High Temperature Ohtaka, Osamu; Fukui, Hiroshi; Kunisada, Taichi Journal of the American Ceramic Society, Vol. 84, Issue 6 https://doi.org/10.1111/j.1151-2916.2001.tb00843.x	journal	June 2001
Polarization switching kinetics of the ferroelectric Al-doped HfO ₂ thin films prepared by atomic layer deposition with different ozone doses Yoon, So-Jung; Na, So-Yeong; Moon, Seung-Eon Journal of Vacuum Science & Technology B, Vol. 37, Issue 5 https://doi.org/10.1116/1.5110621	journal	September 2019
Applications of Modern Ferroelectrics Scott, J. F. Science, Vol. 315, Issue 5814 https://doi.org/10.1126/science.1129564	journal	February 2007
Scale-free ferroelectricity induced by flat phonon bands in HfO ₂ Lee, Hyun-Jae; Lee, Minseong; Lee, Kyoungjun Science, Vol. 369, Issue 6509 https://doi.org/10.1126/science.aba0067	journal	July 2020
Atomic-Level Simulation of Ferroelectricity in Oxides: Current Status and Opportunities Phillpot, Simon R.; Sinnott, Susan B.; Asthagiri, Aravind Annual Review of Materials Research, Vol. 37, Issue 1 https://doi.org/10.1146/annurev.matsci.37.052506.084206	journal	August 2007
Material Aspects in Emerging Nonvolatile Memories Pinnow, Cay-Uwe; Mikolajick, Thomas Journal of The Electrochemical Society, Vol. 151, Issue 6 https://doi.org/10.1149/1.1740785	journal	January 2004
Thermodynamic Stability of High-K Dielectric Metal Oxides ZrO ₂ and HfO ₂ in Contact with Si and SiO2 Gutowski, Maciej; Jaffe, John E.; Liu, Chun-Li MRS Proceedings, Vol. 716 https://doi.org/10.1557/PROC-716-B3.2	journal	January 2002
Review and perspective on ferroelectric HfO2-based thin films for memory applications Park, Min Hyuk; Lee, Young Hwan; Mikolajick, Thomas MRS Communications, Vol. 8, Issue 03 https://doi.org/10.1557/mrc.2018.175	journal	August 2018
Ferroelectric phase stabilization of HfO ₂ by nitrogen doping Xu, Lun; Nishimura, Tomonori; Shibayama, Shigehisa Applied Physics Express, Vol. 9, Issue 9 https://doi.org/10.7567/APEX.9.091501	journal	August 2016
Impact of different dopants on the switching properties of ferroelectric hafniumoxide Schroeder, Uwe; Yurchuk, Ekaterina; Müller, Johannes Japanese Journal of Applied Physics, Vol. 53, Issue 8S1 https://doi.org/10.7567/JJAP.53.08LE02	journal	July 2014

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