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Binary coded cantilevers for enhancing multi-harmonic atomic force microscopy
DOI:10.1016/j.sna.2019.111668.png)
摘要
En 中文
Harmonic atomic force microscopy (AFM) has been widely applied to characterize local mechanical properties of the specimens under imaging. However, the harmonic amplitude is commonly quite weak owing to the fast decay at an off-resonance state for a conventional cantilever and the internal resonance between eigenfrequencies and higher harmonics can amplify the harmonic response. Therefore, specific dynamic characteristics of AFM cantilevers are frequently required. Here, we proposed a coding scheme of a cantilever where the structure is described by a two-dimensional binary matrix to tailor its dynamic characteristics. Genetic algorithms combined with finite element analysis were used to optimize the code configuration. Cantilever properties including eigenfrequencies, stiffness and quality factor can be conveniently tuned to satisfy multiple requirements. AFM cantilevers were then re-designed with the second and the third resonance frequencies being moved to integer multiples of the fundamental one for higher harmonic enhancement, yet with minor stiffness alteration. Harmonic AFM imaging on a polymer mixture demonstrated that the amplitude difference between two material phases was increased up to at least 2.7 times for the 6th harmonic and 1.6 folds for the 18th harmonic using the optimized cantilevers. The enhancement of harmonic contrast can benefit the discrimination of different materials. The proposed binary coding method has advantages such as flexible tailoring of dynamic characteristics, multiple outputs of optimal structures, and automatic optimization. Consequently, it could be a promising way to design cantilevers for enhanced performances in various dynamic AFM imaging applications and also cantilever-based sensing. (C) 2019 Elsevier B.V. All rights reserved.
Keyword:
Atomic force microscopy
Harmonic imaging
Cantilever dynamics
Genetic algorithm
Structural optimization
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期刊
IF:
4.9
论文数:
1.6W
被引数:
3.3W
机构
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