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
基本信息
- 批准号:1752517
- 负责人:
- 金额:$ 53.36万
- 依托单位:
- 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:
- 关键词:
项目摘要
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:材料科学的一个新兴主题是理解和设计表现出生物体特征的人工材料:适应性和进化的功能行为。例子包括图案化的超小天线,其在不同的太阳位置上调制局部电磁场强度,或汽车“皮肤”,其优化车辆在不同环境中的空气动力学。在固态和材料化学计划的支持下,主要研究者的NSF CAREER赠款专注于破译纳米尺寸的构建块自组织和重组成这种自适应材料的规则。选择这些构建块是因为它们具有微型化的独特潜力,以及它们组织成的结构所决定的集体性质。该项目的关键创新有两个方面。首先,一种新型的成像工具将被用来跟踪和录像的积木运动的飞行在原子分辨率。其次,将分析所获得的运动以解释这些构建块之间的串扰。所获得的基本理解也可以应用于由微小基本物体组成的其他系统,例如对人类健康至关重要的生物分子,或者创造可以实现廉价和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“三M实验室”,包括模块化实验室演示,一个移动的游戏应用程序,和电影被用作一个平台,广泛传播给公众。技术摘要:主要研究者的长期目标是将无生命的材料转化为有生命的,能够重新配置其结构和属性的需求。从纳米级构建块设计可重构材料的关键挑战在于理解它们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靶向结构,即构建块纳米级相互作用-靶向结构关系。然而,动力学途径与构建块如何在溶剂中连续扩散和翻滚相关,这在性质上是时空变化的和纳米级的。因此,充分了解这些途径需要具有高时空分辨率的真实空间,原位表征,这是现有的非原位和集成方法所不能提供的。因此,本CAREER提案的研究目标是解决这一挑战,并量化各向异性金纳米颗粒(NP)模型系统中自组装和结构重构的相互作用和动力学途径。所提出的方法是联合收割机的紧急液相透射电子显微镜(TEM)与自动电影分析方法在PI的小组开发的量化NP自组装的动力学。具体而言,本研究将(i)使用具有纳米和毫秒分辨率的低剂量液相TEM捕获代表性各向异性NP的自组装轨迹,(ii)基于这些轨迹的高通量统计分析,从这些轨迹中提取迄今为止的物理参数,例如NP-NP相互作用势和自组装动力学途径,以及(iii)量化不同刺激,例如温度和溶剂极性,影响具有可重构聚合物冠的NP系统中的相变动力学,从而朝向完全自下而上适应其结构和功能的系统移动。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(12)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Nanoscale Cinematography of Soft Matter System under Liquid-Phase TEM
- DOI:10.1021/accountsmr.0c00013
- 发表时间:2020-10
- 期刊:
- 影响因子:0
- 作者:Zihao Ou;Chang Liu;Lehan Yao;Qianmiao Chen
- 通讯作者: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:
- 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:
- 影响因子:2.8
- 作者:Liu, Chang;Ou, Zihao;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:
- 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
Kinetic pathways of crystallization at the nanoscale
- DOI:10.1038/s41563-019-0514-1
- 发表时间:2020-04-01
- 期刊:
- 影响因子:41.2
- 作者:Ou, Zihao;Wang, Ziwei;Chen, Qian
- 通讯作者:Chen, Qian
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Qian Chen其他文献
Molecular Mechanism of Polysaccharides Extracted from Chinese Medicine Targeting Gut Microbiota for Promoting Health
中药多糖靶向肠道菌群促进健康的分子机制
- DOI:
10.1007/s11655-022-3522-y - 发表时间:
2022-05 - 期刊:
- 影响因子:2.9
- 作者:
Wen-Xiao Zhao;Tong Wang;Ya-Nan Zhang;Qian Chen;Yuan Wang;Yan-Qing Xing;Jun Zheng;Chen-Chen Duan;Li-Jun Chen;Hai-Jun Zhao;Shi-Jun Wang - 通讯作者:
Shi-Jun Wang
Synthesis, Structure, and Reactivity of Dicarbene Dipalladium Complexes
二碳烯二钯配合物的合成、结构和反应活性
- DOI:
10.1002/zaac.201200425 - 发表时间:
2013-03 - 期刊:
- 影响因子:1.4
- 作者:
Yunfei Li;Longguang Yang;Qian Chen;Changsheng Cao;Pei Guan;Guangsheng Pang;Yanhui Shi - 通讯作者:
Yanhui Shi
Short-cut waste activated sludge fermentation and application nbsp;of fermentation liquid to improve heterotrophic aerobic nitrogennbsp;removal by Agrobacterium sp. LAD9
废活性污泥的捷径发酵及应用
- DOI:
- 发表时间:
2015 - 期刊:
- 影响因子:15.1
- 作者:
Lina Pang;Jinren Ni;Xiaoyan Tang;Qian Chen - 通讯作者:
Qian Chen
Multiple uncertainty relation for accelerated quantum information
加速量子信息的多重不确定性关系
- DOI:
10.1103/physrevd.102.096009 - 发表时间:
2020-04 - 期刊:
- 影响因子:5
- 作者:
Qian Chen;Wu Ya-Dong;Ji Jia-Wei;Xiao Yunlong;S;ers Barry C. - 通讯作者:
ers Barry C.
A Control Strategy of Islanded Microgrid With Nonlinear Load for Harmonic Suppression
- DOI:
10.1109/access.2021.3064413 - 发表时间:
2021-03 - 期刊:
- 影响因子:3.9
- 作者:
Qian Chen - 通讯作者:
Qian Chen
Qian Chen的其他文献
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{{ truncateString('Qian Chen', 18)}}的其他基金
CAREER: The Regulation of Cytokinesis by Calcium
职业:钙对细胞分裂的调节
- 批准号:
2144701 - 财政年份:2022
- 资助金额:
$ 53.36万 - 项目类别:
Continuing Grant
EAGER: CAS-MNP: Mapping the structure–property relationships of micro- and nanoplastics by in-situ nanoscopic imaging and simulation
EAGER:CAS-MNP:通过原位纳米成像和模拟绘制微米和纳米塑料的结构与性能关系
- 批准号:
2034496 - 财政年份:2020
- 资助金额:
$ 53.36万 - 项目类别:
Standard Grant
EAGER: Neural Behavioral Analysis (NBA) Pipeline for Behavior and Neural Activity Analysis in Autism
EAGER:用于自闭症行为和神经活动分析的神经行为分析 (NBA) 流程
- 批准号:
2035018 - 财政年份:2020
- 资助金额:
$ 53.36万 - 项目类别:
Standard Grant
Research Initiation Award: Towards Realizing a Self-Protecting Healthcare Information System for the Internet of Medical Things
研究启动奖:实现医疗物联网自我保护医疗信息系统
- 批准号:
1700391 - 财政年份:2017
- 资助金额:
$ 53.36万 - 项目类别:
Standard Grant
Research Initiation Award: Towards Realizing a Self-Protecting Healthcare Information System for the Internet of Medical Things
研究启动奖:实现医疗物联网自我保护医疗信息系统
- 批准号:
1812599 - 财政年份:2017
- 资助金额:
$ 53.36万 - 项目类别:
Standard Grant
International Collaboration in Chemistry: Synthesis and Assembly of Shape-Adjustable, Reconfigurable Nanocrystals
化学国际合作:形状可调、可重构纳米晶体的合成和组装
- 批准号:
1303757 - 财政年份:2013
- 资助金额:
$ 53.36万 - 项目类别:
Standard Grant
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