Developing quantitative continuum theories of composite active fluids

发展复合活性流体的定量连续理论

• 批准号: 2202353
• 负责人: Aparna Baskaran
• 金额: $ 33.38万
• 依托单位: Brandeis University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2202353&HistoricalAwards=false
• 关键词: Developing; quantitative; continuum; theories; composite; Developing; quantitative; continuum; theories; composite

NONTECHNICAL SUMMARYThis award supports theoretical, computational, and data-intensive research to develop a theory to describe flow phenomena in biological and other fluids that contain self-powered elements. Flow phenomena in nature and in engineered systems are typically driven by external forces such as gravity and pressure gradients. Continuum mechanics is the mathematical language that allows us to describe such flows and hence predict and design them. In biological systems, such as the cell cytoskeleton, flow phenomena are generated by internal driving, powered by proteins and other biochemical machines that consume chemical energy. Continuum mechanical descriptions have been developed and applied to such internally driven biological fluids in recent years with great success. So far, efforts have centered around single-component descriptions of these systems. In actuality, these are multicomponent systems. Developing multicomponent continuum theories for internally driven fluids requires overcoming several technical challenges. This project uses multi-scale theory coupled with data driven techniques to address these technical challenges and hence develop models for multi-component biological fluids. This project is a step toward understanding physical mechanisms that lead to function in natural and synthetic biological systems. From a practical perspective, designing and controlling internally driven fluids is key to engineering rapidly reconfigurable life-like materials, with applications in fields as diverse as robotics, microfluidics, and adaptive optics. In addition to the science outcomes, the research is integrated with education and outreach initiatives including : (i) content for an advanced undergraduate course on soft materials theory – this fills a need in the education of undergraduate students to undertake interdisciplinary research at the interface of physics and biology and (ii) Diversity, Education and Inclusion initiatives implemented, tested and benchmarked within the Brandeis community that can be exported as models shared widely with the academic community. TECHNICAL SUMMARY This award supports theoretical, computational, and data-intensive research to develop a theoretical framework for building predictive continuum descriptions of composite active fluids. Active fluids are composed of microscopic entities that consume energy and exert forces. This paradigm includes diverse systems from bacterial suspensions to cytoskeletal filaments propelled by molecular motors and synthetic diffusophoretic colloids. Continuum descriptions of the dynamics of these fluids have been powerful in identifying transferable concepts that allow us to understand, control, and even predictively design active fluids. Research to date has focused on single component fluid dynamic descriptions of active materials. But experimental phenomenology clearly shows the need for multi-component descriptions that allow for density gradients in different components. Building macroscopic theories of multi-component systems is challenging even in the context of traditional equilibrating fluids. One needs to invoke considerations of reciprocity and entropy production to determine relationships between different fluxes in the dynamics of conserved quantities. Active fluids, being inherently out of equilibrium are liberated from these constraints. This project addresses these challenges by developing a multi-pronged approach that integrates data driven model development with the standard techniques of soft materials physics. On the one hand, phenomenological continuum mechanics will be combined with systematic nonequilibrium statistical mechanics to identify possible mechanisms at play in determining the emergent behavior in composite active fluids. On the other hand, a complementary data-driven approach is developed, that leverages experimental data from in-vitro cytoskeletal suspension experiments to guide model discovery.This project is aimed to yield fundamental theoretical insights into non-reciprocal cross diffusion processes and their role in emergent behavior in active composite fluids. This effort is a first step in understanding physical mechanisms that lead to function in biological systems. From a practical perspective, designing and controlling active stresses is key to engineering rapidly reconfigurable life-like materials, with applications in fields as diverse as robotics, microfluidics and adaptive optics. The theoretical framework developed in this project will advance our ability to engineer active stress in materials. Integrated with the research effort, this project will produce impact in the community and in physics education through the following initiatives: (i) The development and distribution of content for an advanced undergraduate course on soft materials theory – this fills a need in the education of our undergraduates to undertake interdisciplinary research at the interface of physics and biology. (ii) Outreach initiatives in the Waltham community and beyond – this allows us to work with URM students and reach students in developing countries to expose them to ongoing work in soft materials and biophysics. (iii) Diversity, Education and Inclusion initiatives within the Brandeis community that will serve as a model that can be shared with a wider audience for implementation at other institutions.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.

非技术摘要这一奖项支持理论，计算和数据密集型研究，以开发一种理论来描述生物学和其他包含自动元素的流体中流动现象。自然界和工程系统中的流动现象通常由重力和压力梯度等外力驱动。连续力学是一种数学语言，它使我们能够描述这种流程，从而预测和设计它们。在诸如细胞细胞骨架之类的生物系统中，流动现象是由内部驾驶产生的，由蛋白质和其他食用化学能的生化机器提供动力。近年来，已开发并应用于此类内部驱动的生物学流体，并获得了巨大的成功。到目前为止，努力围绕着这些系统的单一组件描述。实际上，这些是多组分系统。开发用于内部驱动流体的多组分连续性理论需要克服几个技术挑战。该项目使用多尺度理论，再加上数据驱动技术来应对这些技术挑战，从而为多组分生物流体开发模型。该项目是理解导致自然和合成生物学系统功能的物理机制的一步。从实际的角度来看，设计和控制内部驱动的流体是工程迅速重新配置的类似寿命的材料的关键，其应用在机器人技术，微流体和自适应光学等领域中的应用。除了科学的成果外，该研究还与教育和外展计划相结合，包括：（i）在软材料理论上进行高级本科课程的内容 - 这填补了本科生的教育，以在物理和生物学的界面上进行跨学科研究的教育，并随着多样性，教育和包容性的范围，与品牌相关的社区，并进行了典范，并将其与品牌建立在典范中，并进行了典范，并将其与品牌建立在品牌中，并在品牌中实现了品牌，该倡议是在范围内实施的。 社区。技术摘要该奖项支持理论，计算和数据密集型研究，以开发一个理论框架，用于构建复合活性流体的预测性持续描述。活性流体由消耗能量和发挥力的微观实体组成。该范式包括从细菌悬浮液到由分子电动机和合成扩散型胶体推动的细胞骨架细丝的各种系统。这些流体动力学的连续描述在识别可转移的概念方面非常有力，使我们能够理解，控制甚至预测地设计活性流体。迄今为止的研究集中在活动材料的单个组成流体动态描述上。但是实验现象学清楚地表明，需要多组分描述，这些描述允许不同成分中的密度梯度。即使在传统的平衡曲线的背景下，构建多组分系统的宏观理论也受到挑战。人们需要调用互惠和熵产生的考虑，以确定保守数量动力学中不同通量之间的关系。固有地从平衡中固有的活性流体从这些约束中解放出来。该项目通过开发一种多管齐下的方法来解决这些挑战，该方法将数据驱动模型开发与软材料物理的标准技术集成在一起。一方面，现象学连续性力学将与系统的非平衡统计力学相结合，以确定在确定复合活性烟道中的新兴行为时可能发挥的作用。另一方面，开发了一种完整的数据驱动方法，该方法利用了体外细胞骨架悬浮液实验的实验数据来指导模型发现。该项目的目的是产生基本的理论见解，以对非互联体交叉扩散过程及其在活跃组合蝇中的出现行为中的作用。这项工作是理解导致生物系统功能的物理机制的第一步。从实际的角度来看，设计和控制主动应力是工程迅速重新配置的寿命材料的关键，并在机器人技术，微流体和自适应光学等领域中应用。该项目中开发的理论框架将提高我们在材料中设计积极压力的能力。与研究工作集成，该项目将通过以下一项举措对社区和物理教育产生影响：（i）关于软材料理论的高级本科课程的内容的开发和分发 - 这填补了我们本科生的教育（ii）沃尔瑟姆社区的宣传计划的需求（ii）在沃尔瑟姆社区的宣传计划，这使他们可以与他们的材料相处，并在材料中与他们一起工作，并在材料中努力工作，并可以在发展中国家中进行融合，并在发展中国家中融入了众多材料。 （iii）Brandeis社区内的多样性，教育和包容性举措将作为一个模型，可以与其他机构共享更多受众群体以在其他机构实施。该奖项反映了NSF的法定使命，并被认为是通过基金会的知识分子优点和更广泛影响的审查标准来评估通过评估而被认为是珍贵的。