Suppr超能文献

具有定制功能以调节摩擦纳米发电机表面电位的共价有机框架

Covalent Organic Frameworks with Tailored Functionalities for Modulating Surface Potentials in Triboelectric Nanogenerators.

作者信息

Lin Chao, Sun Linhai, Meng Xutong, Yuan Xin, Cui Cheng-Xing, Qiao Huijie, Chen Pengjing, Cui Siwen, Zhai Lipeng, Mi Liwei

机构信息

Henan Key Laboratory of Functional Salt Materials, Center for Advanced Materials Research, Zhongyuan University of Technology, Zhengzhou, 45007, P. R. China.

School of Chemistry and Chemical Engineering, Henan Institute of Science and Technology, Xinxiang, 453003, P. R. China.

出版信息

Angew Chem Int Ed Engl. 2022 Oct 17;61(42):e202211601. doi: 10.1002/anie.202211601. Epub 2022 Sep 19.

Abstract

Designing materials with high triboelectric is an efficient way of improving output performance of triboelectric nanogenerators (TENGs). Herein, we synthesized a series of covalent organic frameworks (COFs) with similar skeletons but various functional groups ranging between electron-donating and electron-withdrawing. These COFs form an ideal platform for clarifying the contribution of each group to TENG performance because the pore wall is perturbed in a predesigned manner. Kelvin probe force microscopy and computational data suggest that surface potentials and electron affinities of COFs can be improved by introducing electron-donating or withdrawing groups, with the highest values observed for fluorinated COF. The TENG with fluorinated COF delivered an output voltage and current of 420 V and 64 μA, respectively, which are comparable to other reported materials. This strategy can be used to efficiently screen suitable frameworks as TENG materials with excellent output performance.

摘要

设计具有高摩擦电性能的材料是提高摩擦电纳米发电机(TENG)输出性能的有效途径。在此,我们合成了一系列具有相似骨架但含有不同供电子和吸电子官能团的共价有机框架(COF)。这些COF构成了一个理想的平台,用于阐明每个基团对TENG性能的贡献,因为孔壁是以预先设计的方式受到扰动的。开尔文探针力显微镜和计算数据表明,通过引入供电子或吸电子基团可以提高COF的表面电位和电子亲和力,其中氟化COF的数值最高。含有氟化COF的TENG分别提供了420 V的输出电压和64 μA的输出电流,这与其他报道的材料相当。该策略可用于有效筛选出具有优异输出性能的合适框架作为TENG材料。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验