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Increasing Imaging Speed and Accuracy in Contact Mode AFM

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Book cover Automation 2019 (AUTOMATION 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 920))

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Abstract

Atomic force microscope (AFM) is a promising tool in micro and nano size objects researches. Contact mode AFM has advantages comparing to non-contact modes: the scanning speed is higher, and atomic resolution can be achieved. The main limiting factor in contact mode AFM is scanning speed. At high scanning speed the ‘loss of contact’ phenomenon occurs, and probe in this case cannot follow the surface. In order to ensure a constant interaction force (stable contact) between the probe and scanned surface, the additional force created by air flow was applied. Proposed method is based on the idea to apply additional controllable nonlinear force on the upper surface of the AFM cantilever, which will help to keep the probe in contact with sample surface. It was found that dynamic characteristics of various AFM sensor cantilevers can be controlled using proposed method. It has been determined that the use of aerodynamic force has the greatest influence on the scanning results deviation from the real sample in the horizontal direction then scanner z axis goes down. With a compressed air pressure of 7 kPa and a scanning speed 847.6 μm/s, this deviation decreases by 20% comparing to the case when compressed air flow is not used.

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Acknowledgement

This research was funded by the European Social Fund according to the activity “Development of Competences of Scientists, other Researchers and Students through Practical Research Activities” of Measure No. 09.3.3-LMT-K-712. Project No 09.3.3-LMT-K-712-02-0137.

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Correspondence to Andrius Dzedzickis .

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Dzedzickis, A., Bučinskas, V., Lenkutis, T., Morkvėnaitė-Vilkončienė, I., Kovalevskyi, V. (2020). Increasing Imaging Speed and Accuracy in Contact Mode AFM. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Automation 2019. AUTOMATION 2019. Advances in Intelligent Systems and Computing, vol 920. Springer, Cham. https://doi.org/10.1007/978-3-030-13273-6_55

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