气候变化领域集成服务门户(CCPortal): Anomalous nanoparticle surface diffusion in LCTEM is revealed by deep learning-assisted analysis

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DOI	10.1073/pnas.2017616118
	Anomalous nanoparticle surface diffusion in LCTEM is revealed by deep learning-assisted analysis
	Jamali V.; Hargus C.; Ben-Moshe A.; Aghazadeh A.; Ha H.D.; Mandadapu K.K.; Alivisatos A.P.
发表日期	2021
ISSN	00278424
卷号	118 期号:10
英文摘要	The motion of nanoparticles near surfaces is of fundamental importance in physics, biology, and chemistry. Liquid cell transmission electron microscopy (LCTEM) is a promising technique for studying motion of nanoparticles with high spatial resolution. Yet, the lack of understanding of how the electron beam of the microscope affects the particle motion has held back advancement in using LCTEM for in situ single nanoparticle and macromolecule tracking at interfaces. Here, we experimentally studied the motion of a model system of gold nanoparticles dispersed in water and moving adjacent to the silicon nitride membrane of a commercial LC in a broad range of electron beam dose rates. We find that the nanoparticles exhibit anomalous diffusive behavior modulated by the electron beam dose rate. We characterized the anomalous diffusion of nanoparticles in LCTEM using a convolutional deep neural-network model and canonical statistical tests. The results demonstrate that the nanoparticle motion is governed by fractional Brownian motion at low dose rates, resembling diffusion in a viscoelastic medium, and continuous-time random walk at high dose rates, resembling diffusion on an energy landscape with pinning sites. Both behaviors can be explained by the presence of silanol molecular species on the surface of the silicon nitride membrane and the ionic species in solution formed by radiolysis of water in presence of the electron beam. © 2021 National Academy of Sciences. All rights reserved.
英文关键词	Anomalous diffusion; Deep neural network; Liquid cell electron microscopy; Single-particle tracking
语种	英语
来源期刊	Proceedings of the National Academy of Sciences of the United States of America
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/180405
作者单位	Department of Chemistry, University of California, Berkeley, CA 94720, United States; Department of Chemical and Biomolecular Engineering, University of California, Berkeley, CA 94720, United States; Materials Science Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, United States; Department of Electrical Engineering and Computer Science, University of California, Berkeley, CA 94720, United States; Chemical Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, United States; Department of Materials Science and Engineering, University of California, Berkeley, CA 94720, United States; Kavli Energy NanoScience Institute, Berkeley, CA 94720, United States
推荐引用方式 GB/T 7714	Jamali V.,Hargus C.,Ben-Moshe A.,et al. Anomalous nanoparticle surface diffusion in LCTEM is revealed by deep learning-assisted analysis[J],2021,118(10).
APA	Jamali V..,Hargus C..,Ben-Moshe A..,Aghazadeh A..,Ha H.D..,...&Alivisatos A.P..(2021).Anomalous nanoparticle surface diffusion in LCTEM is revealed by deep learning-assisted analysis.Proceedings of the National Academy of Sciences of the United States of America,118(10).
MLA	Jamali V.,et al."Anomalous nanoparticle surface diffusion in LCTEM is revealed by deep learning-assisted analysis".Proceedings of the National Academy of Sciences of the United States of America 118.10(2021).