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CAREER: Imaging and Understanding the Kinetic Pathways in Shape-Anisotropic Nanoparticle Self-Assembly

CAREER: Imaging and Understanding the Kinetic Pathways in Shape-Anisotropic Nanoparticle Self-Assembly
职业:成像和理解形状各向异性纳米粒子自组装的动力学路径
批准号:
1752517
负责人:
Qian Chen
金额:
$53.36万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-03-01 至 2023-02-28

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Non-Technical Abstract:An emerging theme in materials science is to understand and design artificial materials exhibiting the features of living organisms: adaptive and evolving functional behaviors. Examples include patterned ultra-small antennas that modulate local electromagnetic field strengths upon different sun positions, or automotive "skins" that optimize the aerodynamics of vehicles in varying environments. With support from the Solid State and Materials Chemistry program, the Principal Investigator's NSF CAREER grant is focused on deciphering the rules upon which nanometer-sized building blocks self-organize and reorganize into such adaptive materials. These building blocks are chosen due to the unique potential for miniaturization and the collective properties determined by the structures they organize into. The key enabling innovations of this project are two-fold. First, a novel imaging tool will be used to trace and videotape the building block motions on the fly at up to atomic resolution. Second, the obtained motions will be analyzed to interpret the crosstalk among these building blocks. The obtained fundamental understanding can also be applied to other systems composed of tiny elementary objects such as biological molecules which are critical for human health, or to create new materials that can achieve cheap and clean renewable energy. The project provides training to both undergraduate and graduate students. A "tri-M lab" including Modular lab demos, a Mobile game app, and Movies is utilized as a platform for broad dissemination to the general public.Technical Abstract:The Principal Investigator's long-term goal is to transmute inanimate materials into animate ones, capable of reconfiguring their structure and property on demand. The key challenge in designing reconfigurable materials from nanoscale building blocks lies in understanding the kinetic pathways of their self-assembly. These pathways define how building blocks interact and assemble into targeted structures, i.e. the building block nanoscale interaction-targeted structure relationship. However, the kinetic pathways are associated with how building blocks continuously diffuse and tumble in a solvent, which is both spatiotemporally varying and nanoscopic in nature. Thus, fully understanding these pathways requires real-space, in-situ characterization with high spatiotemporal resolution, which is not offered by existing ex-situ and ensemble methods. The research objective of this CAREER proposal is thus to address this challenge and to quantify the interactions and kinetic pathways governing self-assembly and structural reconfiguration in model systems of anisotropic gold nanoparticles (NPs). The proposed approach is to combine the emergent liquid-phase transmission electron microscopy (TEM) with automated movie analysis methods developed in the PI's group to quantify the dynamics of NP self-assembly. Specifically, this research will (i) capture the self-assembly trajectories of representative anisotropic NPs using low-dose liquid-phase TEM with nanometer and millisecond resolution, (ii) extract from these trajectories hitherto physical parameters, such as NP-NP interaction potentials and self-assembly kinetic pathways, based on high-throughput statistical analysis of these trajectories, and (iii) quantify how diverse stimuli, such as temperature and solvent polarity, affect phase transition dynamics in systems of NPs with reconfigurable polymer coronas, moving towards systems that adapt their structure and functions entirely from the bottom-up. This approach will help establish a quantitative building block-nanoscale interaction-targeted structure relationship for predictive materials design.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(12)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1021/accountsmr.0c00013
发表时间: 2020-10
期刊:
影响因子: --
作者: [Zihao Ou;Chang Liu;Lehan Yao;Qianmiao Chen]
通讯作者: Zihao Ou;Chang Liu;Lehan Yao;Qianmiao Chen
DOI: 10.1038/s41467-019-09787-6
发表时间: 2019-04-18
期刊: NATURE COMMUNICATIONS
影响因子: 16.6
作者: [Luo, Binbin, Kim, Ahyoung, Chen, Qian]
通讯作者: Chen, Qian
Direct imaging on the deformation and sintering of polymeric particles at the nanoscale by liquid-phase TEM
利用液相 TEM 对纳米级聚合物颗粒的变形和烧结进行直接成像
DOI: 10.1017/s1431927621009326
发表时间: 2021
期刊: Microscopy and Microanalysis
影响因子: 2.8
作者: [Liu, Chang, Ou, Zihao, Chen, Qian]
通讯作者: Chen, Qian
DOI: 10.1021/acscentsci.0c00430
发表时间: 2020-07
期刊: ACS Central Science
影响因子: 18.2
作者: [Lehan Yao;Zihao Ou;Binbin Luo;Cong Xu;Qian Chen]
通讯作者: Lehan Yao;Zihao Ou;Binbin Luo;Cong Xu;Qian Chen
9
    CAREER: The Regulation of Cytokinesis by Calcium
    • 批准号:
      2144701
    • 项目类别:
      Continuing Grant
    • 资助金额:
      $70.09万
    • 财政年份:
      2022
    • 负责人:
      Qian Chen
    • 依托单位:
    EAGER: CAS-MNP: Mapping the structure–property relationships of micro- and nanoplastics by in-situ nanoscopic imaging and simulation
    EAGER: Neural Behavioral Analysis (NBA) Pipeline for Behavior and Neural Activity Analysis in Autism
    Research Initiation Award: Towards Realizing a Self-Protecting Healthcare Information System for the Internet of Medical Things
    • 批准号:
      1700391
    • 项目类别:
      Standard Grant
    • 资助金额:
      $30.0万
    • 财政年份:
      2017
    • 负责人:
      Qian Chen
    • 依托单位:
    国内基金
    海外基金
    非小细胞肺癌Biomarker的Imaging MS研究新方法
    • 批准号:
      30672394
    • 项目类别:
      面上项目
    • 资助金额:
      30.0万元
    • 批准年份:
      2006
    • 负责人:
      陆豪杰
    • 依托单位: