Rapid Online Quantification of Tip-Sample Interaction for High-Speed Dynamic-Mode Atomic Force Microscope Imaging

被引:0
|
作者
Busch, David [1 ]
Ren, Juan [2 ]
Zou, Qingze [2 ]
Ganapathysubramanian, Baskar [1 ]
机构
[1] Iowa State Univ, Dept Mech Engn, Ames, IA 50011 USA
[2] Rutgers State Univ, Mech & Aerosp Engn Dept, Piscataway, NJ 08854 USA
关键词
MOLECULES; EVOLUTION;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
his paper presents a numerical-experimental integrated framework for rapid online estimation of the tip sample interaction forces for high speed AFM dynamic imaging. Quantifying the tip-sample interaction in AFM dynamic imaging is crucial towards achieving high-speed dynamic-mode AFM imaging with minimized tip-sample forces, particularly when imaging live biological samples in liquid media. Large tip-sample interactions can result in sample deformation or even destruction of the live biological samples. In this article, we propose an ultra-fast inversion strategy based on parallel algorithms implemented on Graphical Processing Units (GPUs). The tip-sample interaction estimation problem is posed as an inverse problem and is solved in near-real time using GPUs. We investigate several cost-functional formulations to ensure quality of reconstruction while maintaining a high rate of reconstruction. The computational scheme is verified with preliminary experimental results. his paper presents a numerical-experimental integrated framework for rapid online estimation of the tip sample interaction forces for high speed AFM dynamic imaging. Quantifying the tip-sample interaction in AFM dynamic imaging is crucial towards achieving highspeed dynamic-mode AFM imaging with minimized tip-sample forces, particularly when imaging live biological samples in liquid media. Large tip-sample interactions can result in sample deformation or even destruction of the live biological samples. In this article, we propose an ultra-fast inversion strategy based on parallel algorithms implemented on Graphical Processing Units (GPUs). The tip-sample interaction estimation problem is posed as an inverse problem and is solved in near-real time using GPUs. We investigate several cost-functional formulations to ensure quality of reconstruction while maintaining a high rate of reconstruction. The computational scheme is verified with preliminary experimental results. T
引用
收藏
页码:2879 / 2884
页数:6
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