TY - JOUR
T1 - Optimization of Ferroelectric Properties of HfO2-Based Thin Films by Ion Irradiation
AU - Liao, Ningtao
AU - Lin, Xin
AU - Zhu, Bingyan
AU - Zhong, Xiangli
AU - Jiang, Limei
AU - Ouyang, Xiaoping
N1 - Publisher Copyright:
© 1963-2012 IEEE.
PY - 2024/5/1
Y1 - 2024/5/1
N2 - In order to explore ion irradiation optimization schemes for HfO2-based ferroelectric films, this article combines the Monte Carlo (MC) method with the phase-field method to establish a multiscale model that correlates micro vacancy and macro ferroelectric properties of thin films. This study indicates that ions, such as He, Ar, and Fe, can optimize the ferroelectric properties of thin films, while H ions are unsuitable for irradiation optimization. The synergistic effect of concentration and distribution of ion-induced ion oxygen vacancies is the key microscopic factor affecting the film's ferroelectric properties. Oxygen vacancy defects with a concentration of 1 × 1022 cm-3 and uniform distribution could maximize the optimization of thin film's ferroelectric performance. Oxygen vacancy's concentration and distribution are, respectively, mainly determined by the ion dose and type. Adjusting the incidence angle of ion can, to some extent, solve the problem of uneven distribution of oxygen vacancies. Through extensive simulation analysis, we found that Ar ions, when administered at an incidence energy of 400 keV and dosage of 5 × 1015 ions/cm2, exhibit the most significant optimization effect on the ferroelectric properties of the thin film, resulting in a remarkable 46% increase in remanent polarization compared to the pre-irradiation state. This work elucidates the fundamental principles of optimizing the ferroelectric properties of HfO2 -based thin films by ion irradiation and provides appropriate irradiation conditions, thus offering theoretical support for experimental endeavors in ion irradiation-based modification and optimization.
AB - In order to explore ion irradiation optimization schemes for HfO2-based ferroelectric films, this article combines the Monte Carlo (MC) method with the phase-field method to establish a multiscale model that correlates micro vacancy and macro ferroelectric properties of thin films. This study indicates that ions, such as He, Ar, and Fe, can optimize the ferroelectric properties of thin films, while H ions are unsuitable for irradiation optimization. The synergistic effect of concentration and distribution of ion-induced ion oxygen vacancies is the key microscopic factor affecting the film's ferroelectric properties. Oxygen vacancy defects with a concentration of 1 × 1022 cm-3 and uniform distribution could maximize the optimization of thin film's ferroelectric performance. Oxygen vacancy's concentration and distribution are, respectively, mainly determined by the ion dose and type. Adjusting the incidence angle of ion can, to some extent, solve the problem of uneven distribution of oxygen vacancies. Through extensive simulation analysis, we found that Ar ions, when administered at an incidence energy of 400 keV and dosage of 5 × 1015 ions/cm2, exhibit the most significant optimization effect on the ferroelectric properties of the thin film, resulting in a remarkable 46% increase in remanent polarization compared to the pre-irradiation state. This work elucidates the fundamental principles of optimizing the ferroelectric properties of HfO2 -based thin films by ion irradiation and provides appropriate irradiation conditions, thus offering theoretical support for experimental endeavors in ion irradiation-based modification and optimization.
KW - Computational material science
KW - HfO2-based materials
KW - ferroelectric thin film
KW - ion implantation
KW - oxygen vacancy
KW - radiation dosage
KW - transformation behavior
UR - https://www.scopus.com/pages/publications/85189323866
U2 - 10.1109/TNS.2024.3383160
DO - 10.1109/TNS.2024.3383160
M3 - 文章
AN - SCOPUS:85189323866
SN - 0018-9499
VL - 71
SP - 1208
EP - 1217
JO - IEEE Transactions on Nuclear Science
JF - IEEE Transactions on Nuclear Science
IS - 5
M1 - 3383160
ER -