In an atomic force microscope (AFM) system, the measurement accuracy in the scan images is determined by the displacement accuracy of piezo scanner. The hysteresis model of piezo scanner displacement is complex and difficult to correct, which is the main reason why the output displacement of the piezo scanner does not have high precision. In this study, an image pixel hysteresis model of the piezo scanner displacement in the AFM system was established. An AFM was used to scan a two-dimensional (2D) grating in the 0 ° and 90 ° directions and a polynomial fitting method was employed to obtain the image pixel hysteresis model parameters of the piezo scanner displacement in the X-direction and Y-direction. The image pixel hysteresis model was applied to correct the AFM scan image of regular octagons. The results showed that the relative measurement error in the X-direction was decreased from 12.47% to 0.52% after the correction and that in the Y-direction decreased from 28.57% to 0.35%. The image pixel hysteresis model can be applied in the post-processing software of a commercial AFM system. The model solves the hysteresis problem of the AFM system and improves the measuring accuracy of AFM in 2 degrees of freedom (2 DOF).
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http://dx.doi.org/10.1016/j.ultramic.2020.112992 | DOI Listing |
J Microsc
January 2025
Department of Mechanical, Materials and Aerospace Engineering, University of Liverpool, Liverpool, UK.
Electron backscatter diffraction (EBSD) has developed over the last few decades into a valuable crystallographic characterisation method for a wide range of sample types. Despite these advances, issues such as the complexity of sample preparation, relatively slow acquisition, and damage in beam-sensitive samples, still limit the quantity and quality of interpretable data that can be obtained. To mitigate these issues, here we propose a method based on the subsampling of probe positions and subsequent reconstruction of an incomplete data set.
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School of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, Republic of Korea.
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January 2025
The Academy of Applied Technical and Preschool Studies, Aleksandra Medvedeva 20, 18000 Nis, Serbia.
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Institute of Mechanical Engineering and Energy Technology, Lucerne University of Applied Sciences and Arts, CH-6048 Horw, Switzerland.
Automated agricultural robots are becoming more common with the decreased cost of sensor devices and increased computational capabilities of single-board computers. Weeding is one of the mundane and repetitive tasks that robots could be used to perform. The detection of weeds in crops is now common, and commercial solutions are entering the market rapidly.
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December 2024
Institute of Smart Systems and Services, Pforzheim University, 75175 Pforzheim, Germany.
Multispectral imaging (MSI) enables non-invasive tissue differentiation based on spectral characteristics and has shown great potential as a tool for surgical guidance. However, adapting MSI to open surgeries is challenging. Systems that rely on light sources present in the operating room experience limitations due to frequent lighting changes, which distort the spectral data and require countermeasures such as disruptive recalibrations.
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