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Conference Paper: Study of nano-manipulation approach based on the least action principle using AFM based robotic system

TitleStudy of nano-manipulation approach based on the least action principle using AFM based robotic system
Authors
Issue Date2017
PublisherInstitute of Electrical and Electronics Engineers. The Journal's web site is located at https://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1001331
Citation
Proceedings of 2017 36th Chinese Control Conference (CCC), Dalian, China, 26-28 July 2017, p. 4424-4429 How to Cite?
AbstractAtomic force microscopy (AFM) is originally used to observe the sample surface, and then extended to the area of nano-manipulation. It can be quite valuable in the further study of maneuvering nano-particles. Because of the influence of the tip morphology on the tip pushing direction, it is difficult to establish an effective operating model for stably manipulating nanoparticles with controllable manipulation results. To resolve this problem, the acting force of manipulating the nano-particle is analyzed firstly based on the least action principle. Then the influence of the contact point between the nano-particle and the tip is taken into account on the pushing direction, and manipulation of the nano-particle is modeled to predict its position after manipulation. Next, the model parameter is calibrated through several tests. Finally, the proposed model is verified by assembling the nano-structure. The experimental results illustrate that the model can effectively predict the nano-particle position after maneuvering, and can improve the manipulation efficiency.
Persistent Identifierhttp://hdl.handle.net/10722/262548
ISSN

 

DC FieldValueLanguage
dc.contributor.authorYuan, S-
dc.contributor.authorLiu, L-
dc.contributor.authorWang, Z-
dc.contributor.authorXi, N-
dc.contributor.authorWang, Y-
dc.date.accessioned2018-09-28T05:01:12Z-
dc.date.available2018-09-28T05:01:12Z-
dc.date.issued2017-
dc.identifier.citationProceedings of 2017 36th Chinese Control Conference (CCC), Dalian, China, 26-28 July 2017, p. 4424-4429-
dc.identifier.issn1934-1768-
dc.identifier.urihttp://hdl.handle.net/10722/262548-
dc.description.abstractAtomic force microscopy (AFM) is originally used to observe the sample surface, and then extended to the area of nano-manipulation. It can be quite valuable in the further study of maneuvering nano-particles. Because of the influence of the tip morphology on the tip pushing direction, it is difficult to establish an effective operating model for stably manipulating nanoparticles with controllable manipulation results. To resolve this problem, the acting force of manipulating the nano-particle is analyzed firstly based on the least action principle. Then the influence of the contact point between the nano-particle and the tip is taken into account on the pushing direction, and manipulation of the nano-particle is modeled to predict its position after manipulation. Next, the model parameter is calibrated through several tests. Finally, the proposed model is verified by assembling the nano-structure. The experimental results illustrate that the model can effectively predict the nano-particle position after maneuvering, and can improve the manipulation efficiency.-
dc.languageeng-
dc.publisherInstitute of Electrical and Electronics Engineers. The Journal's web site is located at https://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1001331-
dc.relation.ispartof2017 36th Chinese Control Conference (CCC)-
dc.rightsChinese Control Conference. Copyright © Institute of Electrical and Electronics Engineers.-
dc.rights©2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.titleStudy of nano-manipulation approach based on the least action principle using AFM based robotic system-
dc.typeConference_Paper-
dc.identifier.emailXi, N: xining@hku.hk-
dc.identifier.authorityXi, N=rp02044-
dc.identifier.doi10.23919/ChiCC.2017.8028055-
dc.identifier.hkuros292780-
dc.identifier.spage4424-
dc.identifier.epage4429-
dc.publisher.placeUnited States-

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