Collaborative Research: DMREF: Synthetic machines from feedback-controlled active matter

非技术描述：生物细胞表现出显著的功能，如运动、分裂和自我修复。在合成材料中复制这些栩栩如生的行为将给工程学带来革命性的变化，并推动基础科学的发展。由运动的耗能微观单元组成的活性流体是实现这些雄心勃勃目标的一个有希望的平台。与被广泛研究的传统被动材料不同，活性流体会产生内力，驱动持续的自主运动，这是一种诱人的仿生特征。然而，就其本身而言，散装活性流体表现出混乱的流动。因此，它们不能执行诸如产生功或驱动净材料运输等有用的功能。通过无缝融合实验、理论和机器学习方法，该项目旨在利用活性流体的混沌动力学来实现功能行为。特别是，该项目将测量光响应活动流体的瞬时构型，并使用依赖模型的理论和/或独立于模型的机器学习方法来预测其演变动力学。这些信息将施加理论指导的外部信号，将系统引导到目标状态，例如包裹体的持续旋转或包裹活性流体的可变形液滴的细胞状持续爬行。该项目还将开展几项紧密结合的教育和外联活动，重点是(1)向研究生和本科生提供跨学科科学方面的严格培训和指导，(2)鼓励代表性不足的群体从事STEM相关领域的工作，(3)向更广泛的社区提高对科学研究重要性的普遍认识。技术描述：通过控制产生力量的细胞骨架与周围可变形的脂膜之间的相互作用，生物细胞实现了显著的功能。受此观察启发，该项目将追求两个相辅相成的目标，即使用基于光响应微管的活性流体来控制刚性和可变形界面和包裹体的动力学和运动。这代表着朝着创造合成生命类材料和机器迈出了第一步。第一个目标是将孤立的刚性包裹体嵌入到光敏活性向列相液晶中。活动流体产生的应力对包裹体施加随机力，驱动包裹体的动力学。其目的是实现理论-实验混合反馈，通过施加活动应力的时空模式来驱动目标包裹体动力学。第二个目标是将光响应性活性流体封装在由传统液-液相分离产生的可变形液滴中。在均匀光照下(因此活性均匀)，活性液滴表现出栩栩如生的形态变化和活性诱导的扩散，但与生物细胞不同的是，它没有定向运动。实施的反馈方案将控制活性液滴的形成、运动、融合和分解。该项目将按照DMREF计划的设想，通过在从秒到分钟的单个实验中实施迭代理论/实验反馈周期，开发独特的响应和适应性材料。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Non-technical Description: Biological cells exhibit remarkable functionalities, such as motility, division, and self-healing. Reproducing these life-like behaviors in synthetic materials would both revolutionize engineering and advance fundamental science. Active fluids, which are composed of motile energy-consuming microscopic units, are a promising platform for achieving these ambitious goals. In contrast to widely studied conventional passive materials, active fluids generate internal forces that drive persistent autonomous motion, an alluring life-like feature. On their own, however, bulk active fluids exhibit chaotic flows. Thus, they are unable to perform useful functions such as generating work or driving net material transport. By seamlessly merging experiments, theory and machine learning methods, this project aims to harness the chaotic dynamics of active fluids to achieve functional behaviors. In particular, the project will measure the instantaneous configuration of a light-responsive active fluid and use model-dependent theory and/or model-independent machine-learning methods to forecast its evolving dynamics. This information will impose theory-guided external signals that steer the system toward a targeted state such as a persistent rotation of an inclusion or cell-like persistent crawling of a deformable droplet that encapsulates an active fluid. The project will also pursue several tightly integrated education and outreach activities focused on (1) providing rigorous training and mentoring in interdisciplinary sciences to graduate and undergraduate students, (2) encouraging underrepresented groups to pursue work in STEM-related fields, (3) and raising general awareness of the importance of scientific research to broader communities. Technical Description: By controlling interactions between the force-generating cytoskeleton and the surrounding deformable lipid membrane, biological cells achieve remarkable functionalities. Inspired by this observation, this project will pursue two complementary aims that use light-responsive microtubule-based active fluids to control the dynamics and motions of rigid and deformable interfaces and inclusions. This represents a first step toward creating synthetic life-like materials and machines. The first aim will embed an isolated rigid inclusion into a photo-responsive active nematic liquid crystal. The stresses generated by the active fluid exert stochastic forces on the inclusion, driving its dynamics. The aim is to implement hybrid theory-experiment feedback to drive the targeted inclusion dynamics by imposing spatiotemporal patterns of active stress. The second aim will encapsulate light-responsive active fluids within deformable droplets created by conventional liquid-liquid phase separation. Under uniform illumination (thus uniform activity), active droplets exhibit life-like morphological shape changes and activity-induced spreading, but unlike biological cells have no directional motion. The implemented feedback scheme will control the formation, motility, fusion, and breakup of the active droplets. The project will develop unique responsive and adaptive materials as envisioned by the DMREF program, by implementing iterative theory/experiment feedback cycles during a single experiment on timescales of seconds to minutes.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.