Unraveling the origins of ferroelectricity in doped hafnia through carrier-mediated phase transitions

IF 11.9 1区 材料科学 Q1 CHEMISTRY, PHYSICAL npj Computational Materials Pub Date : 2025-02-15 DOI:10.1038/s41524-025-01515-7
Gang Li, Shaoan Yan, Yulin Liu, Wanli Zhang, Yongguang Xiao, Qiong Yang, Minghua Tang, Jiangyu Li, Zhilin Long
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Abstract

Doping is critical for inducing ferroelectricity in hafnia films, yet the underlying mechanisms remain debated. Here, through first-principles studies, we elucidate the pivotal role played by the complex phase transition mechanisms under carrier doping in understanding the origin of hafnia ferroelectricity. Specifically, electron doping orchestrates a metastable polar phase to stable antipolar phase transformation, driven by strong screening effects and weakened nonpolar covalent bonds, making n-type dopants rare. Conversely, weak screening effect and enhanced polar covalent bonding strengthen robust ferroelectricity, enabling significant ground-state phase transitions from the monoclinic to the polar orthorhombic phase and finally to the cubic phase under hole doping, a phenomenon prevalent in hafnia-based films doped with p-type dopants. Furthermore, this hole-enhanced polar distortion also results in an inverse size effect in hafnia ferroelectric films, unlike perovskite ferroelectrics. Our findings offer new insights into the preparation of robust hafnia-based ferroelectric films through doping or interface engineering.

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通过载流子介导的相变揭示掺杂铪中铁电性的起源
掺杂是诱导铪膜铁电性的关键,但其潜在机制仍存在争议。通过第一性原理研究,我们阐明了载流子掺杂下的复杂相变机制在理解半铁电的起源中所起的关键作用。具体来说,电子掺杂在强大的筛选效应和减弱的非极性共价键的驱动下,协调了亚稳极性相到稳定反极性相的转变,使n型掺杂物变得罕见。相反,弱的筛选效应和增强的极性共价键增强了强大的铁电性,使得基态相变从单斜相到极性正交相,最后到空穴掺杂下的立方相,这是掺杂p型掺杂剂的半铪基薄膜中普遍存在的现象。此外,与钙钛矿铁电体不同,这种空穴增强的极性畸变也会在半氟铁电膜中产生逆尺寸效应。我们的发现为通过掺杂或界面工程制备坚固的铪基铁电薄膜提供了新的见解。
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来源期刊
npj Computational Materials
npj Computational Materials Mathematics-Modeling and Simulation
CiteScore
15.30
自引率
5.20%
发文量
229
审稿时长
6 weeks
期刊介绍: npj Computational Materials is a high-quality open access journal from Nature Research that publishes research papers applying computational approaches for the design of new materials and enhancing our understanding of existing ones. The journal also welcomes papers on new computational techniques and the refinement of current approaches that support these aims, as well as experimental papers that complement computational findings. Some key features of npj Computational Materials include a 2-year impact factor of 12.241 (2021), article downloads of 1,138,590 (2021), and a fast turnaround time of 11 days from submission to the first editorial decision. The journal is indexed in various databases and services, including Chemical Abstracts Service (ACS), Astrophysics Data System (ADS), Current Contents/Physical, Chemical and Earth Sciences, Journal Citation Reports/Science Edition, SCOPUS, EI Compendex, INSPEC, Google Scholar, SCImago, DOAJ, CNKI, and Science Citation Index Expanded (SCIE), among others.
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