SELF-ASSEMBLY OF ACTIVE NANOPARTICLES

自然界使用自组装来产生各种各样的功能结构。这个过程利用热运动来产生纳米结构，几乎没有外部成本。不幸的是，必须依赖于随机运动的缺点，而不是故意的演习，是所有的纳米组件将不加区别地找到彼此，而不一定匹配正确的合作伙伴。在过去的几年里，已经合成了一种新的纳米颗粒。通过将分散在溶液中的化学燃料转化为一致的定向运动，这些粒子有效地表现为纳米火箭（自推进粒子），并代表细菌的合成模拟物。使用理论和计算技术的结合，PI的团队将研究这种新的令人兴奋的功能（推进）如何不仅可以为创造具有不寻常机械性能的新型功能材料提供通用平台，而且还可以通过有效降低其复杂性来大大简化或偏向与自组装过程相关的动力学景观。该奖项支持了一系列的推广活动，包括开发触摸屏设备的教育软件，对研究生和本科生进行理论和数值研究的培训，以及其他旨在扩大科学和工程领域代表性不足的群体参与的教育活动。技术摘要该奖项支持了一个计算，理论和教育计划，以研究自推进纳米粒子如何自组装。在自推进粒子系统中出现的集体行为是非常独特的，让人想起一些鸟类（群集）、昆虫（群集）和鱼类（集群）所表现出的美丽的相关运动。由活性成分形成的凝聚相的材料特性也令人兴奋和非常不寻常，为下一代智能材料的发展带来了希望。该提案有两个主要目标：（1）了解非活性系统（可用作固体热力学参考）中非常基本和公认的现象如何在不同程度的活性施加于纳米颗粒时继续进行;从而引导更好地理解活性和热力学之间的相互作用，这是这些系统中观察到的现象学行为的核心。(2)开发策略来控制活性纳米组分如何自组装，并将其随机主动运动转化为它们形成的介观结构的相干运动，从而创建可以通过利用纳米级化学燃料（或其他能源）来执行工作的活性聚集体。

Nontechnical SummaryNature uses self-assembly to generate a vast variety of functional structures. This process leverages thermal motion to generate nanostructures at practically no external cost. Unfortunately, the drawback of having to rely on random motion, as opposed to deliberate maneuvers, is that all nanocomponents will indiscriminately find each other without necessarily matching the correct partners. Over the last few years, a new kind of nanoparticle has been synthesized. By converting chemical fuel dispersed in solution into consistent, directed motion, these particles behave effectively as nano-rockets (self-propelled particles), and represent the synthetic analog of bacteria. Using a combination of theoretical and computational techniques, the PI's group will study how this new exciting feature (propulsion), not only could provide a general platform for creating novel functional materials with unusual mechanical properties, but also, how it could greatly simplify or bias the dynamical landscape associated with the self-assembly processes, by effectively reducing its complexity. This award supports a number of outreach initiatives, including the development of educational software for touch screen devices, training of graduate and undergraduate students in theoretical and numerical research, and other educational activities aimed at broadening participation of underrepresented groups in science and engineering.Technical SummaryThis award supports a computational, theoretical and educational program to study how self-propelled nanoparticles self-assemble. The collective behavior that emerges in systems of self-propelled particles is quite unique, and is reminiscent of the beautiful correlated motion exhibited by some birds (flocking), insects (swarming) and fish (schooling). The material properties of condensed phases formed by active components are also exciting and very unusual, holding promise for the development of the next generation of intelligent materials. This proposal has two main goals: (1) To understand how very basic and well-established phenomena in non-active systems (that can be used as a solid thermodynamic reference) carry over when different degrees of activity are imposed on the nanoparticles; thus leading the way to a better understanding of the interplay between active and thermal forces that is at the core of the phenomenological behavior observed in these systems. (2) To develop strategies to control how active nanocomponents self-assemble, and transform their random active motion into a coherent motion of the mesoscopic structures they form, thus creating active aggregates that can perform work by exploiting chemical fuel (or other sources of energy) at nanoscale.