Statistical morphological identification of low-dimensional nanomaterials by using TEM

doi:10.1016/j.partic.2021.03.0131674-2001

IMR OpenIR

	Statistical morphological identification of low-dimensional nanomaterials by using TEM
	Pu, Yinghui 1,2; Niu, Yiming 1,2; Wang, Yongzhao 1,2; Liu, Siyang 1; Zhang, Bingsen 1,2
通讯作者	Zhang, Bingsen(bszhang@imr.ac.cn)
	2022-02-01
发表期刊	PARTICUOLOGY
ISSN	1674-2001
卷号	61 页码:11-17
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/).
关键词	Low-dimensional nanomaterials Transmission electron microscopy ZnO Selected area electron diffraction X-ray diffraction
资助者	National Natural Science Foundation of China ; LiaoNing Revitalization Talents Program ; ResearchFund of SYNL ; Postdoctoral Science Foundation of China
DOI	10.1016/j.partic.2021.03.0131674-2001
收录类别	SCI
语种	英语
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
WOS类目	Engineering, Chemical ; Materials Science, Multidisciplinary
WOS记录号	WOS:000720795500001
出版者	ELSEVIER SCIENCE INC
引用统计	被引频次：15[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.imr.ac.cn/handle/321006/167363
专题	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.