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

合作研究：DMREF：反馈控制活性物质的合成机器

• 批准号: 2324195
• 负责人: Michael Hagan
• 金额: $ 63万
• 依托单位: Brandeis University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2027-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2324195&HistoricalAwards=false
• 关键词: Collaborative; Research; DMREF; Synthetic; machines

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.

非技术性描述：生物细胞具有显著的功能，如运动，分裂和自我修复。在合成材料中再现这些类似生命的行为将彻底改变工程技术，并推动基础科学的发展。活性流体是由运动的耗能微观单元组成的，是实现这些雄心勃勃的目标的一个有前途的平台。与广泛研究的传统被动材料相比，主动流体产生内部力量，驱动持续的自主运动，这是一种诱人的生命特征。然而，本体活性流体本身表现出混沌流动。因此，它们不能执行有用的功能，例如产生功或驱动净材料运输。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主动流体的瞬时配置，并使用模型相关理论和/或模型无关机器学习方法来预测其演变动力学。该信息将施加理论引导的外部信号，该外部信号将系统转向目标状态，诸如包封活性流体的可变形液滴的内含物的持续旋转或细胞状持续爬行。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）为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）提高公众对科学研究对更广泛社区重要性的认识。 技术说明：通过控制产生力的细胞骨架和周围可变形脂质膜之间的相互作用，生物细胞实现了显着的功能。受这一观察的启发，该项目将追求两个互补的目标，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。这代表了创造合成生命材料和机器的第一步。第一个目标是将一个孤立的刚性夹杂物嵌入到光响应的活性液晶中。由活动流体产生的应力对夹杂物施加随机力，从而驱动其动力学。其目的是实现混合理论-实验反馈，通过施加主动应力的时空模式来驱动有针对性的包含动力学。第二个目标是将光响应活性流体封装在由常规液-液相分离产生的可变形液滴内。在均匀照明（因此均匀活动）下，活性液滴表现出类似生命的形态形状变化和活动诱导的扩散，但与生物细胞不同，它们没有定向运动。所实施的反馈方案将控制活性液滴的形成、运动性、融合和分裂。该项目将按照DMREF计划的设想，通过在几秒到几分钟的时间尺度上的单个实验中实施迭代理论/实验反馈周期，开发出独特的响应性和适应性材料。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。