CIF: Small: Collaborative Research: Signal processing for enabling high speed probe based nanoimaging

纳米科学和纳米技术的一个关键推动者是原子力显微镜（AFM），它开辟了在原子尺度上询问和操纵物质的新领域。它在理解亚原子分子结构、蛋白质折叠动力学和材料表征方面取得了突破。基于AFM的成像速度显著加快的潜在影响是巨大的，例如，它将允许在纳米尺度上研究材料的动力学，这是迄今为止无法实现的。本研究的目的是研究现代信号处理技术，实现成像速度的一个数量级的增益。研究人员将通过学生访问和专业研讨会推动工程和AFM社区之间的技术协同转移。这些发现将在适当的水平上融入本科生和研究生课程。AFM的主要组成部分是一个悬臂梁，它会在皮牛顿尺度的力作用下发生偏转。本研究的重点是动态模式AFM操作，其中悬臂轻轻地点击被成像的样品;用于成像生物样品的模式的选择。尽管力确实形成了样品形貌的良好指标，但AFM系统动力学的系统存储器和非线性排除了将悬臂力直接映射到形貌的更精细描述中，特别是在高成像速度下。研究人员以数学上易于处理的方式对复杂的纳米级相互作用进行建模，以促进样品特征的最大后验（MAP）序列检测的发展。因子图表示和适当的推理方案的发展将进行研究。该算法将在FPGA上实现，并通过实验数据进行详尽的测试。

A key enabler of Nanoscience and Nanotechnology is the Atomic Force Microscope (AFM) that has opened up new realms, of interrogation and manipulation of matter at the atomic scale. It has resulted in breakthroughs in understanding sub-atomic molecular structure, protein folding dynamics and materials characterization. The potential impact of significantly faster AFM based imaging is immense, e.g., it will allow the study of dynamics of material at the nanoscale that was hitherto not accessible. The aim of this research is to study modern signal processing techniques that achieve gains in imaging speeds by an order of magnitude. The investigators will push the synergistic transfer of knowhow between the engineering and the AFM communities through student visits and specialized workshops. The findings will be integrated at appropriate levels into the undergraduate and graduate curriculum.The main component of an AFM is a cantilever that deflects in response to forces at the pico-Newton scale. The focus of this research is the dynamic mode AFM operation, where the cantilever gently taps the sample being imaged; the mode of choice for imaging biological samples. Even though forces do form a good indicator of sample topography, the system memory and the nonlinearities of the AFM system dynamics preclude a direct mapping of the cantilever forces into a finer description of topography, especially at high imaging speeds. The investigators model the complex nanoscale interactions in a mathematically tractable manner that facilitates the development of maximum a posteriori (MAP) sequence detection of the sample features. Factor graph representations and the development of appropriate inference schemes will be studied. The algorithms will be implemented on FPGAs and tested exhaustively with experimental data.