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Book Chapter: AFM Image Reconstruction Using Compensation Model of Thermal Drift

TitleAFM Image Reconstruction Using Compensation Model of Thermal Drift
Authors
Issue Date2020
PublisherSpringer Nature
Citation
AFM Image Reconstruction Using Compensation Model of Thermal Drift. In Shuai Yuan, Lianqing Liu, Zhidong Wang, Ning Xi (Eds.), AFM-Based Observation and Robotic Nano-manipulation, p. 49-81. Singapore: Springer Nature, 2020 How to Cite?
AbstractThe system thermal drift is an uncertain factor in the scanning of the AFM image. Thermal drift is difficult to be detected by using traditional sensor. Therefore, digital image method is adopted to perform correction. Currently, the correction accuracy is not high and this correction method cannot be widely used to solve the system thermal drift. In this chapter, according to the scanning characteristics of the tip driver, the influence of thermal drift on the scanning process is analyzed, and the thermal drift deformation model of the AFM image is established. The characteristic region offset vectors in the AFM image are solved by mathematical method. The offset vectors of other non-characteristic regions in the image are calculated according to the characteristic region offset vectors. The whole scanning image is reconstructed to improve the global image accuracy.
Persistent Identifierhttp://hdl.handle.net/10722/283024
ISBN

 

DC FieldValueLanguage
dc.contributor.authorYuan, S-
dc.contributor.authorLiu, L-
dc.contributor.authorWang, Z-
dc.contributor.authorXi, N-
dc.date.accessioned2020-06-05T06:24:09Z-
dc.date.available2020-06-05T06:24:09Z-
dc.date.issued2020-
dc.identifier.citationAFM Image Reconstruction Using Compensation Model of Thermal Drift. In Shuai Yuan, Lianqing Liu, Zhidong Wang, Ning Xi (Eds.), AFM-Based Observation and Robotic Nano-manipulation, p. 49-81. Singapore: Springer Nature, 2020-
dc.identifier.isbn9789811505072-
dc.identifier.urihttp://hdl.handle.net/10722/283024-
dc.description.abstractThe system thermal drift is an uncertain factor in the scanning of the AFM image. Thermal drift is difficult to be detected by using traditional sensor. Therefore, digital image method is adopted to perform correction. Currently, the correction accuracy is not high and this correction method cannot be widely used to solve the system thermal drift. In this chapter, according to the scanning characteristics of the tip driver, the influence of thermal drift on the scanning process is analyzed, and the thermal drift deformation model of the AFM image is established. The characteristic region offset vectors in the AFM image are solved by mathematical method. The offset vectors of other non-characteristic regions in the image are calculated according to the characteristic region offset vectors. The whole scanning image is reconstructed to improve the global image accuracy.-
dc.languageeng-
dc.publisherSpringer Nature-
dc.relation.ispartofAFM-Based Observation and Robotic Nano-manipulation-
dc.titleAFM Image Reconstruction Using Compensation Model of Thermal Drift-
dc.typeBook_Chapter-
dc.identifier.emailXi, N: xining@hku.hk-
dc.identifier.authorityXi, N=rp02044-
dc.identifier.doi10.1007/978-981-15-0508-9_3-
dc.identifier.hkuros310028-
dc.identifier.spage49-
dc.identifier.epage81-
dc.publisher.placeSingapore-

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