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: University of Illinois at Urbana-Champaign
• 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
• 起止时间: 2018-03-01 至 2023-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1752517&HistoricalAwards=false
• 关键词: CAREER; Imaging; Understanding; Kinetic; Pathways

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.

非技术摘要：材料科学中的一个新兴主题是理解和设计具有生物特征的人造材料：适应性和不断发展的功能行为。例子包括图案化的超小型天线，这些天线调节不同的太阳位置上的局部电磁场强度，或者在不同环境中优化车辆的空气动力学的汽车“皮肤”。在固态和材料化学计划的支持下，首席研究员的NSF职业赠款专注于破译纳米尺寸的构件自我组织并重组此类自适应材料的规则。选择这些构建块是由于小型化的独特潜力以及由它们组织成的结构确定的集体特性。该项目的创新启用的关键是两个方面。首先，一种新颖的成像工具将用于跟踪和录像原子分辨率的构件动作。其次，将分析获得的动议，以解释这些构件之间的串扰。所获得的基本理解也可以应用于由小型基本物体组成的其他系统，例如生物分子，这些物体对人类健康至关重要，或者创建可以实现廉价且可清洁的可再生能源的新材料。该项目为本科生和研究生提供培训。一个“ Tri-M Lab”，包括模块化实验室演示，手机游戏应用程序和电影，被用作广泛传播给公众的平台。技术摘要：主要研究者的长期目标是将无生命的材料传输到动画材料中，能够按需重新配置其结构和财产。从纳米级构建块设计可重构材料的主要挑战在于了解其自组装的动力学途径。这些途径定义了构建块如何相互作用并组装成目标结构，即构建块纳米级相互作用的结构关系。但是，动力学途径与构建块在溶剂中连续扩散和翻滚的方式有关，溶剂的自然界既有空间变化又是纳米镜的。因此，充分理解这些途径需要具有高时空分辨率的真实空间，原位表征，这不是现有的前坐标和集合方法提供的。因此，这项职业建议的研究目标是应对这一挑战，并量化各向异性金纳米颗粒（NPS）模型系统中的自组装和结构重新配置的相互作用和动力学途径。提出的方法是将新兴的液相透射电子显微镜（TEM）与PI组中开发的自动电影分析方法相结合，以量化NP自组装的动力学。具体而言，这项研究将（i）使用低剂量的液态液相和纳米分辨率和毫秒分辨率捕获代表性各向异性NP的自组装轨迹，（ii）从迄今轨迹的物理参数中提取的提取物，例如NP-NP相互作用和自我组装的Kinetic Pathways，基于高量化的统计分析，II这些型号分析以及（II刺激（例如温度和溶剂极性）会影响NPS系统中具有可重构聚合物冠状动脉的NPS的相变动力学，从而朝着完全从自下而上调整其结构和功能的系统。这种方法将有助于建立针对预测材料设计的定量构件纳米级互动的结构关系。该奖项反映了NSF的法定任务，并且使用基金会的智力优点和更广泛的影响审查标准，被认为值得通过评估来获得支持。

项目成果

Nanoscale Cinematography of Soft Matter System under Liquid-Phase TEM

• DOI: 10.1021/accountsmr.0c00013
• 发表时间: 2020-10
• 作者: Zihao Ou;Chang Liu;Lehan Yao;Qianmiao Chen

Hierarchical self-assembly of 3D lattices from polydisperse anisometric colloids

• 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

Kinetic pathways of crystallization at the nanoscale

• DOI: 10.1038/s41563-019-0514-1
• 发表时间: 2020-04-01
• 期刊: NATURE MATERIALS
• 影响因子: 41.2
• 作者: Ou, Zihao;Wang, Ziwei;Chen, Qian
• 通讯作者: Chen, Qian

Machine Learning to Reveal Nanoparticle Dynamics from Liquid-Phase TEM Videos

• 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

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