SELF-ASSEMBLY OF ACTIVE NANOPARTICLES

大自然使用自组装来产生各种各样的功能结构。该工艺利用热运动来产生纳米结构，几乎没有外部成本。不幸的是，依赖随机运动的缺点，而不是刻意的操作，是所有的纳米组件将不加选择地找到彼此，而不一定匹配正确的伙伴。在过去的几年里，一种新的纳米粒子被合成出来。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），并代表了细菌的合成模拟物。利用理论和计算技术的结合，PI的团队将研究这个令人兴奋的新特性（推进）如何不仅可以为创造具有不同寻常机械性能的新型功能材料提供一个通用平台，而且还可以通过有效降低其复杂性来极大地简化或倾向于与自组装过程相关的动态景观。该奖项支持多项推广活动，包括为触摸屏设备开发教育软件，培训研究生和本科生进行理论和数值研究，以及旨在扩大未被充分代表的群体参与科学和工程的其他教育活动。该奖项支持一项计算、理论和教育计划，研究自推进纳米粒子如何自组装。在自我推进的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（成群）、昆虫（成群）和鱼（成群）所表现出的美丽的相关运动。由活性组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。这一建议有两个主要目标：(1)了解当不同程度的活性施加在纳米颗粒上时，非活性系统（可作为固体热力学参考）中非常基本和公认的现象是如何延续的；这样就可以更好地理解在这些系统中观察到的现象学行为的核心——活动力和热力之间的相互作用。(2)开发控制活性纳米组分自组装的策略，并将其随机主动运动转化为其形成的介观结构的相干运动，从而创造出可以利用化学燃料（或其他能源）在纳米尺度上工作的活性聚集体。

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.