首页|Extraction algorithm for longitudinal and transverse mechanical information of AFM

Extraction algorithm for longitudinal and transverse mechanical information of AFM

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The atomic force microscope (AFM) can measure nanoscale morphology and mechanical properties and has a wide range of applications. The traditional method for measuring the mechanical properties of a sample does so for the longitudinal and transverse properties separately, ignoring the coupling between them. In this paper, a data processing and multidimensional mechanical information extraction algorithm for the composite mode of peak force tapping and torsional resonance is proposed. On the basis of a tip–sample interaction model for the AFM, longitudinal peak force data are used to decouple amplitude and phase data of transverse torsional resonance, accurately identify the tip–sample longitudinal contact force in each peak force cycle, and synchronously obtain the corresponding characteristic images of the transverse amplitude and phase. Experimental results show that the measured longitudinal mechanical characteristics are consistent with the transverse amplitude and phase characteristics, which verifies the effectiveness of the method. Thus, a new method is provided for the measurement of multidimensional mechanical characteristics using the AFM.

Atomic force microscopePeak force tappingTorsional resonanceMechanical characteristic measurementBackground subtraction algorithmCoupled mechanical model

Chunxue Hao、Shoujin Wang、Shuai Yuan、Boyu Wu、Peng Yu、Jialin Shi

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School of Information and Control Engineering,Shenyang Jianzhu University,Shenyang 110168,China

State Key Laboratory of Robotics,Shenyang Institute of Automation,Chinese Academy of Sciences,Shenyang 110016,China

Institute of Robotics and Intelligent Manufacturing Innovation,Chinese Academy of Sciences,Shenyang 110169,China

General Program of the National Natural Science Foundation of China国家自然科学基金国家自然科学基金

620732276192780561903359

2022

纳米技术与精密工程(英文)
中国微米纳米技术学会,天津大学

纳米技术与精密工程(英文)

CSTPCDCSCDEI
影响因子：0.476
ISSN：1672-6030
年,卷(期)：2022.5(2)
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