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

摘要：材料科学的一个新兴主题是理解和设计具有生物体特征的人工材料：适应性和进化的功能行为。例子包括在不同太阳位置调制局部电磁场强度的图案超小型天线，或在不同环境中优化车辆空气动力学的汽车“皮肤”。在固态和材料化学项目的支持下，首席研究员的NSF职业生涯资助重点是破译纳米级构建块自组织和重组成这种自适应材料的规则。这些建筑模块的选择是由于其独特的小型化潜力和由其组织结构决定的集体属性。这个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追踪和录像构建块运动在飞行中高达原子分辨率。其次，将分析获得的运动来解释这些构件之间的串扰。获得的基本理解也可以应用于其他由微小基本物体组成的系统，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可再生能源的新材料。该项目为本科生和研究生提供培训。包括模块化实验室演示、手机游戏应用程序和电影在内的“tri-M实验室”被用作向公众广泛传播的平台。技术摘要：首席研究员的长期目标是将无生命的物质转化为有生命的物质，能够根据需要重新配置其结构和属性。从纳米级构建块设计可重构材料的关键挑战在于理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-目标结构关系。然而，动力学途径与构建块在溶剂中如何持续扩散和翻滚有关，这既是时空变化的，也是纳米级的。因此，充分理解这些途径需要高时空分辨率的实时空间、原位表征，而现有的非原位和集成方法无法提供这一点。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（NPs）模型系统中控制自组装和结构重构的相互作用和动力学途径。提出的方法是将涌现的液相透射电子显微镜（TEM）与PI小组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。具体来说，本研究将(i)利用纳米和毫秒分辨率的低剂量液相透射电镜捕捉具有代表性的各向异性纳米粒子的自组装轨迹，（ii）从这些轨迹中提取迄今为止的物理参数，如NP-NP相互作用势和自组装动力学路径，基于这些轨迹的高通量统计分析，以及（iii）量化不同的刺激，如温度和溶剂极性，影响具有可重构聚合物电晕的NPs系统的相变动力学，朝着完全自底向上适应其结构和功能的系统发展。这种方法将有助于为预测材料设计建立定量的构建块-纳米级相互作用目标结构关系。该奖项反映了美国国家科学基金会的法定使命，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。

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.