Zhen Wu, Guoliang Liu, Jie Liang, Tianqi Wei, Ning Xu
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引用次数: 0
Abstract
The unique optical, electrical, and thermal properties of 1D nanowires have sparked significant interest in growing high-quality 1D materials. Nanowire arrays and aligned growth offer scalability and maintain anisotropic properties, making them promising for research and applications. However, mass-producing high-quality nanowire arrays remains a challenge. A strategy is proposed for growing nanowire arrays based on homogeneous precursor as the substrate. Both calculations and experiments demonstrate that using a self-assembly micro-platform in advance facilitates epitaxial growth via chemical vapor deposition (CVD) to achieve highly oriented nanowire arrays. This is attributed to changes in crystallographic disregistry and adhesion energy. For instance, SnTe nanowire arrays are successfully grown using this method, with significantly lower thermal conductivity (≈5.5 W m−1 K−1 at 300 K) compared to the bulk material (≈9.1 W m−1 K−1 at 300 K), making them ideal for thermoelectric applications. The research lays the foundation for the tunable growth of IV–VI nanowire arrays and opens up possibilities for innovative thermoelectric nano–micro devices.
一维纳米线独特的光学、电学和热性能引起了人们对高质量一维材料的极大兴趣。纳米线阵列和排列生长提供了可扩展性和保持各向异性的特性,使它们在研究和应用中具有前景。然而,大规模生产高质量的纳米线阵列仍然是一个挑战。提出了一种以均质前驱体为衬底生长纳米线阵列的方法。计算和实验都表明,预先使用自组装微平台可以通过化学气相沉积(CVD)实现外延生长,从而实现高度定向的纳米线阵列。这是由于晶体失配和粘附能的变化。例如,使用这种方法可以成功地生长出SnTe纳米线阵列,与大块材料(300 K时≈9.1 W m-1 K-1)相比,其导热系数(300 K时≈5.5 W m-1 K-1)显着降低,使其成为热电应用的理想选择。该研究为IV-VI纳米线阵列的可调生长奠定了基础,并为创新的热电纳米微器件开辟了可能性。
Small MethodsMaterials 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.