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Statistical morphological identification of low-dimensional nanomaterials by using TEM
Pu, Yinghui1,2; Niu, Yiming1,2; Wang, Yongzhao1,2; Liu, Siyang1; Zhang, Bingsen1,2
刊名PARTICUOLOGY
2022-02-01
卷号61页码:11-17
关键词Low-dimensional nanomaterials Transmission electron microscopy ZnO Selected area electron diffraction X-ray diffraction
ISSN号1674-2001
DOI10.1016/j.partic.2021.03.0131674-2001
通讯作者Zhang, Bingsen(bszhang@imr.ac.cn)
英文摘要Nanomaterials with low-dimensional morphology display unique properties in catalysis and related fields, which are highly dependent on the structure and aspect ratio. Thus, accurate identification of the structure and morphology is the basis to correlate to the performance. However, the widely adopted techniques such as XRD is incapable to precise identify the aspect ratio of low-dimensional nanomaterials, not even to quantify the morphological uniformity with statistical deviation value. Herein, ZnO nanorod and nanosheet featured with one-and two-dimensional morphology were selected as model materi-als, which were prepared by the hydrothermal method and statistically characterized by transmission electron microscopy (TEM). The results indicate that ZnO nanorods and nanosheets display rod-like and orthohexagnal morphology, which mainly encapsulated with {100} and {001} planes, respectively. The 7.36 +/- 0.20 and 0.39 +/- 0.02 aspect ratio (c/a) of ZnO nanorods and nanosheets could be obtained through the integration of the (100) and (002) diffraction rings in selected area electron diffraction (SAED). TEM combining with the SAED is favorable compare with XRD, which not only provides more accurate aspect ratio results with standard deviation values but also requires very small amounts of sample. This work is supposed to provide a convenient and accurate method for the characterization of nanomaterials with low-dimensional morphology through TEM. (c) 2021 Chinese Society of Particuology and Institute of Process Engineering, Chinese Academy of Sciences. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
资助项目National Natural Science Foundation of China[22072164] ; National Natural Science Foundation of China[22002173] ; National Natural Science Foundation of China[51932005] ; National Natural Science Foundation of China[21773269] ; National Natural Science Foundation of China[21761132025] ; LiaoNing Revitalization Talents Program[XLYC 1807175] ; ResearchFund of SYNL ; Postdoctoral Science Foundation of China[2020M680999]
WOS研究方向Engineering ; Materials Science
语种英语
出版者ELSEVIER SCIENCE INC
WOS记录号WOS:000720795500001
资助机构National Natural Science Foundation of China ; LiaoNing Revitalization Talents Program ; ResearchFund of SYNL ; Postdoctoral Science Foundation of China
内容类型期刊论文
源URL[http://ir.imr.ac.cn/handle/321006/167362]  
专题金属研究所_中国科学院金属研究所
通讯作者Zhang, Bingsen
作者单位1.Chinese Acad Sci, Inst Met Res, Shenyang Natl Lab Mat Sci, Shenyang 110016, Peoples R China
2.Univ Sci & Technol China, Sch Mat Sci & Engn, Shenyang 110016, Peoples R China
推荐引用方式
GB/T 7714
Pu, Yinghui,Niu, Yiming,Wang, Yongzhao,et al. Statistical morphological identification of low-dimensional nanomaterials by using TEM[J]. PARTICUOLOGY,2022,61:11-17.
APA Pu, Yinghui,Niu, Yiming,Wang, Yongzhao,Liu, Siyang,&Zhang, Bingsen.(2022).Statistical morphological identification of low-dimensional nanomaterials by using TEM.PARTICUOLOGY,61,11-17.
MLA Pu, Yinghui,et al."Statistical morphological identification of low-dimensional nanomaterials by using TEM".PARTICUOLOGY 61(2022):11-17.
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