选择性激光掺杂与脱掺杂在二氧化钒薄膜相工程中的应用。

IF 10.7 2区 材料科学 Q1 CHEMISTRY, PHYSICAL
Small Methods Pub Date : 2025-01-01 Epub Date: 2024-11-28 DOI:10.1002/smtd.202400832
He Ma, Yuan Li, Jianhua Hao, Yonghuang Wu, Run Shi, Ruixuan Peng, Linbo Shan, Yimao Cai, Kechao Tang, Kai Liu, Xinping Zhang
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引用次数: 0

摘要

二氧化钒(VO2)以其金属到绝缘体的可逆转变(MIT)而闻名,在可配置光子和电子器件中得到了广泛的应用。精确地在微/纳米尺度上裁剪VO2的MIT对于小型化和集成设备至关重要。然而,现有的裁剪技术,如扫描探针显微镜,尽管精度很高,但效率和适应性不足,特别是在复杂或弯曲的表面上。本文采用激光写入辅助氢掺杂或脱掺杂的方法,高效地实现了VO2薄膜相的局部工程。激光掺杂和激光脱掺杂技术也具有高度的灵活性,可以制造可重构、非易失性和多功能的VO2器件。该方法为创建可重构微/纳米光子和微/纳米电子器件建立了新的范例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Selective Laser Doping and Dedoping for Phase Engineering in Vanadium Dioxide Film.

Vanadium dioxide (VO2), renowned for its reversible metal-to-insulator transition (MIT), has been widely used in configurable photonic and electronic devices. Precisely tailoring the MIT of VO2 on micro-/nano-scale is crucial for miniaturized and integrated devices. However, existing tailoring techniques like scanning probe microscopy, despite their precision, fall short in efficiency and adaptability, particularly on complex or curved surfaces. Herein, this work achieves the local engineering of the phase of VO2 films in high efficiency by employing laser writing to assist in the hydrogen doping or dedoping process. The laser doping and laser dedoping technique is also highly flexible, enabling the fabrication of reconfigurable, non-volatile, and multifunctional VO2 devices. This approach establishes a new paradigm for creating reconfigurable micro/nanophotonic and micro/nanoelectronic devices.

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来源期刊
Small Methods
Small Methods Materials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍: Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques. With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community. The online ISSN for Small Methods is 2366-9608.
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