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arXiv 2404.07166cond-mat.mtrl-sci
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利用低能 Ar+ 辐照对六方氮化硼进行缺陷工程

Defect-engineering hexagonal boron nitride using low-energy Ar+ irradiation

Manuel Längle, Barbara Maria Mayer, Jacob Madsen, Diana Propst, Arixin Bo, Clara Kofler, Vinzent Hana, Clemens Mangler, Toma Susi, Jani Kotakoski

AI总结:

该研究利用低能 Ar+ 辐照对悬浮单层 hBN 进行缺陷工程,通过自动化 STEM 定量比较辐照前后缺陷浓度与类型,证明简单离子辐照已具备缺陷类型选择性。

摘要:

单层六方氮化硼(hBN)近来作为承载量子发射体的材料成为密集研究的焦点。尽管众所周知,此类发射与点缺陷相关,但迄今为止尚未证明光谱与特定缺陷之间存在确定性关联。在此,我们制备了原子级清洁的悬浮 hBN 样品,并对其进行低能离子辐照。通过自动化扫描透射电子显微镜成像,在辐照前后对样品进行表征,以评估缺陷浓度和分布。我们发现本征缺陷浓度约为 0.03/nm²(其中约 55% 为硼单空位,8% 为氮单空位,20% 为双空位,16% 为更复杂的空位结构)。为了能够区分这些缺陷与辐照诱导缺陷,我们利用离子产生了显著更高(但仍适中)的缺陷浓度(0.30/nm²),此时发现约 55% 为硼单空位,12% 为氮单空位,14% 为双空位,18% 为更复杂的空位结构。结果表明,即便是最简单的辐照也能提供对缺陷类型的选择性,并为未来通过改变辐照参数来探索改变选择性的实验开辟了道路。

英文摘要:

Monolayer hexagonal boron nitride (hBN) has recently become the focus of intense research as a material to host quantum emitters. Although it is well known that such emission is associated with point defects, so far no conclusive correlation between the spectra and specific defects has been demonstrated. Here, we prepare atomically clean suspended hBN samples and subject them to low-energy ion irradiation. The samples are characterized before and after irradiation via automated scanning transmission electron microscopy imaging to assess the defect concentrations and distributions. We find an intrinsic defect concentration of ca. 0.03/nm2 (with ca. 55% boron and 8% nitrogen single vacancies, 20% double vacancies and 16% more complex vacancy structures). To be able to differentiate between these and irradiation-induced defects, we create a significantly higher (but still moderate) concentration of defects with the ions (0.30/nm2), and now find ca. 55% boron and 12% nitrogen single vacancies, 14% double vacancies, and 18% more complex vacancy structures. The results demonstrate that already the simplest irradiation provides selectivity for the defect types, and open the way for future experiments to explore changing the selectivity by modifying the irradiation parameters.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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