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Control-Based Adaptive Characterization of Nano-scale Mechanical and Structural Properties of Biological Materials

Control-Based Adaptive Characterization of Nano-scale Mechanical and Structural Properties of Biological Materials
基于控制的生物材料纳米级机械和结构特性的自适应表征
批准号:
1634592
负责人:
Juan Ren
金额:
$34.6万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-09-01 至 2022-02-28

项目摘要

项目成果

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中文摘要
翻译
这个项目的目标是同时绘制机械性能,并表征结构,使用扫描探针显微镜(SPM)的生物样品。SPM的主要部分是一个悬臂,它可以被想象成一个微型跳水板,其尖端附着在自由端的底部。当样品在尖锐的尖端下通过时,悬臂的固定端以受控的方式上下移动。该项目面临的挑战是,从悬臂梁上下移动时弯曲的方式推断样品的表面形貌和机械性能,以及样品在其下方移动。提取这些数据是具有挑战性的,因为很难将移动表面施加的力的不同组成部分的影响分开。由于需要避免损坏脆弱样品的操作限制,以及有时需要在液体环境中对样品进行表征,SPM在生物材料上的使用进一步复杂化。该项目考虑了如何根据悬臂响应调整激励运动,以提供最佳测量。生物样品力学特性的变化与许多疾病的进展有关,包括纤维化、癌症的发生和转移。可靠地测量这些特性的能力将推进这些疾病的诊断测试。该项目包括在爱荷华州立大学(Iowa State University)建立的项目下,通过参观和演讲,向中学生和高中生推广。本项目旨在利用基于控制的方法,提高扫描探针显微镜(SPM)在多种生物材料的孔隙和粘弹性制图中的性能并建立新的功能。具体目标是:(1)制定具有最佳激励力设计的纳米力学表征方法,以激发样品的粘弹性和孔隙弹性行为;(2)基于最优输出过渡设计,构建了一种基于控制的自适应SPM成像技术,实现了样品变形量化和实时力速优化;(3)通过制定新的基于数据驱动的反演控制方法来补偿动力学耦合和系统不确定性,实现高速纳米力学性能映射;(4)实现并评估SPM纳米力学性能制图方案,开发集成软件平台,实现SPM制图与基于光学的生物结构定量同步。
英文摘要
The goal of this project is to simultaneously map the mechanical properties, and characterize the structure, of a biological sample using a scanning probe microscope (SPM). The main part of the SPM is a cantilever, that may be visualized as a miniature diving board with a sharp tip attached to the underside of the free end. The fixed end of the cantilever is moved up and down in a controlled way, as a sample is passed under the sharp tip. The challenge addressed by this project is to infer both the surface topography and the mechanical properties of the sample from the way the cantilever bends as it is moved up and down, and the sample moves beneath it. Extracting this data is challenging, because it can be difficult to separate the influences of the different components of the forces exerted by the moving surface. Use of the SPM on biological materials is further complicated by operational limits needed to avoid damaging delicate samples, and by the need to sometimes characterize samples in a liquid environment. This project considers how the excitation motion may be adjusted based on the cantilever response to provide the best possible measurement. Changes in mechanical properties of biological samples have been related to the progression of numerous diseases, including fibrosis, cancer initiation and metastasis. The ability to reliably measure these properties will advance diagnostic tests for these conditions. The project includes outreach to middle- and high-school students through tours and presentations under well-established programs at Iowa State University. This project aims to improve the performance and build new functions of scanning probe microscopes (SPM) in poro- and visco- elasticity mapping of a broad variety of biological materials, using control-based approaches. The specific objectives are to (1) formulate a nanomechanical characterization methodology with optimal excitation force design to enable excitation of sample visco- and poro- elastic behavior; (2) build a new control-based adaptive SPM imaging technique with sample deformation quantification and real time force and speed optimization based on optimal output transition design; (3) achieve high-speed nanomechanical property mapping through formulating new data-driven inversion-based control approach to compensate for dynamics coupling and system uncertainty; and (4) implement and evaluate the nanomechanical property mapping scheme on SPM and then to develop an integrated software platform to synchronize the SPM mapping with optical-based bio-structure quantification.
期刊论文(18)
专著(0)
科研奖励(0)
会议论文
DOI: 10.3390/ijms21020392
发表时间: 2020-01-02
期刊: INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
影响因子: 5.6
作者: [Liu, Yi, Mollaeian, Keyvan, Ren, Juan]
通讯作者: Ren, Juan
Tracking Control Using Recurrent-neural-network-based Inversion Model: a Case Study on a Piezo Actuator
使用基于循环神经网络的反演模型进行跟踪控制:压电执行器的案例研究
DOI: 10.1109/tie.2020.3037989
发表时间: 2020
期刊: IEEE Transactions on Industrial Electronics
影响因子: 7.7
作者: [Xie, Shengwen, Ren, Juan]
通讯作者: Ren, Juan
Iterative Learning-based Model Predictive Control for Precise Trajectory Tracking of Piezo Nanopositioning Stage
基于迭代学习的模型预测控制,用于压电纳米定位台的精确轨迹跟踪
DOI: 10.23919/acc.2018.8430854
发表时间: 2018
期刊: 2018 Annual American Control Conference (ACC
影响因子: --
作者: [Xie, Shengwen, Ren, Juan]
通讯作者: Ren, Juan
DOI: 10.23919/acc45564.2020.9147964
发表时间: 2019-12
期刊: 2020 American Control Conference (ACC)
影响因子: --
作者: [S. Xie;Juan Ren]
通讯作者: S. Xie;Juan Ren
共 15 条
    Student Travel Support for the 2023 IEEE/ASME International Conference on Advanced Intelligent Mechatronics; Seattle, Washington; June 28 to July 1, 2023
    • 批准号:
      2245052
    • 项目类别:
      Standard Grant
    • 资助金额:
      $2.08万
    • 财政年份:
      2023
    • 负责人:
      Juan Ren
    • 依托单位:
    CAREER: Modeling and Control of Cellular Response to Dynamic Mechanical Manipulation Using a Dual-Input Platform
    • 批准号:
      1751503
    • 项目类别:
      Standard Grant
    • 资助金额:
      $50.0万
    • 财政年份:
      2018
    • 负责人:
      Juan Ren
    • 依托单位:
    国内基金
    海外基金
    Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
    Incentive and governance schenism study of corporate green washing behavior in China: Based on an integiated view of econfiguration of environmental authority and decoupling logic
    • 批准号:
      --
    • 项目类别:
      外国学者研究基金项目
    • 资助金额:
      --
    • 批准年份:
      2024
    • 负责人:
      YU BYUNGJUN
    • 依托单位:
    Exploring the Intrinsic Mechanisms of CEO Turnover and Market Reaction: An Explanation Based on Information Asymmetry
    • 批准号:
      W2433169
    • 项目类别:
      外国学者研究基金项目
    • 资助金额:
      --
    • 批准年份:
      2024
    • 负责人:
      HAOFEI ZHANG
    • 依托单位:
    A study on prototype flexible multifunctional graphene foam-based sensing grid (柔性多功能石墨烯泡沫传感网格原型研究)
    • 批准号:
      --
    • 项目类别:
      --
    • 资助金额:
      20万元
    • 批准年份:
      2020
    • 负责人:
      SAGAR RIZWAN UR REHMAN
    • 依托单位: