Weili Cui, Wendi Zhang, Kunpeng Tang, Yingzhi Chen, Kecheng Cao, Lei Shi, Guowei Yang
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引用次数: 0
Abstract
Armchair graphene nanoribbons (AGNRs) known as semiconductors are holding promise for nanoelectronics applications and sparking increased research interest. Currently, synthesis of 5-AGNRs with a quasi-metallic gap has been achieved using perylene and its halogen-containing derivatives as precursors via on-surface synthesis on a metal substrate. However, challenges in controlling the polymerization and orientation between precursor molecules have led to side reactions and the formation of by-products, posing a significant issue in purity. Here a precision synthesis of confined 5-AGNRs using molecular-designed precursors without halogens is proposed to address these challenges. Perylene and its dimer quaterrylene are utilized for filling into single-walled carbon nanotubes (SWCNTs), following a precursor-driven transition into 5-AGNRs by heat-induced polymerization and cyclodehydrogenation. SWCNTs restrict the alignment of confined quaterrylene enabling their polymerization with a head-to-tail arrangement, which results in the formation of pure 5-AGNRs with three times higher yield than that of perylene, as the free rotation capability of perylene molecules inside SWCNTs lead to the formation of 5-AGNRs concomitant with by-products. This work provides a templated route for synthesizing desired GNRs based on molecular-designed precursors and confined polymerization, bringing advantages for their applications in electronics and optoelectronics.
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.