CAREER: Self-organization and shape change in elastic active matter

非技术总结这个职业奖项支持理论和计算研究，以描述和理解受生物启发的活性固体的行为。这项研究中开发的模型是由细胞、细胞骨架和多细胞组织中发生的生物物质的机械力驱动的形状变化所驱动的。在组织发育和细胞迁移等关键的生物过程中，生物物质利用化学模式的机械力以编程和强大的方式改变形状。因此，它们是活性物质的极好例子，活性物质由微观成分组成，消耗能量来产生机械力和运动。与组成成分自由移动的活性流体不同，生物材料通常包含相互连接的聚合物网络，这些聚合物通过像弹性弹簧一样变形来响应机械力。此外，与普通固体不同，普通固体在外力作用下变形，以达到明确定义的最低能量状态，活动固体的力产生单元嵌入材料本身，并可以通过它们本身产生的变形进行重新分配。这些独特的特性使活性固体能够自主地产生热力学平衡下普通固体所没有的图案和形状。PI和他的研究团队将通过结合机械和化学因素来创建形状变化的活性固体的理论和计算模型。其总体目标是从理论和计算上研究活性固体中可能出现的独特的形状变化和自组织现象。结果将与从PI的合作者那里获得的细胞骨架材料和血液凝块的实验数据进行比较。我们的研究将为细胞生物学和组织形态发生中的自组织提供基本的理解。它可能会影响组织工程学的策略，以及能够自主改变形状的合成软材料的设计。教育和外展活动与这项研究相结合。这些课程的重点是为多个层次的学生创造独特的跨学科学习机会，包括计算。PI将(1)为高中生提供暑期计算讲习班；(2)为生命科学专业的入门物理课程以及核心物理课程开发计算模块；以及(3)通过暑期桥模块培训初学研究生科学计算基础知识。这些教育和外展努力将有助于在加利福尼亚州服务不足的圣华金山谷和其他地区招聘和培训未来的STEM劳动力。技术总结这个职业奖支持通过生物启发的机械力-化学反馈在弹性活性物质中发展自发形状变化和自组织的物理理论。它还支持国际学生联合会的教育倡议，通过跨学科生物物理模型在多个水平上培训学生进行科学计算。活性物质是指消耗化学能并产生机械力和运动的实体的集合。与含有自推进颗粒的活性流体不同，活性固体包含通过弹性弹簧类约束连接的成分，这些成分表现出变形，而不是响应机械力的大规模流动。在生物中，这些机械力是由分子马达产生的，分子马达的活动是由化学信号决定的。这项研究将受到发生在细胞骨架和多细胞组织中的生命物质固有的机械力-化学性质的启发。Pi和他的研究团队将开发一类结合了主动机械力、弹性变形、取向有序和化学梯度以及它们之间的相互作用的模型，导致自发的形状变化和图案形成。PI的团队将专注于两个对机械力敏感的非线性机械系统：弹性薄壳由于其固有的几何非线性而通过屈曲经历3D形状变化，以及无序的纤维网络，呈现复杂的非线性变形模式。将使用互补的建模策略，包括适用于理论分析的连续介质模型，以及用于数值计算的离散网络模型。这项研究将揭示生物的弹性形变如何有助于1)几何和应变对化学浓度的调节；2)活动单元之间的相互弹性相互作用将其自组织动力学驱动到有序状态；3)通过形变诱导排列的长程取向有序及其相关的拓扑缺陷；以及4)通过各种屈曲不稳定性产生的复杂的三维形状。PI提出了一项综合教育计划，涉及从K-12到本科生和研究生的多个级别的计算培训。这将通过1)为K-12学校学生设计的暑期计算讲习班和演示；2)生命科学专业的入门物理课程和核心物理课程的计算模块；以及3)通过夏季桥梁计划培训初学研究生的计算技能。这些教育和外展活动将有助于在加利福尼亚州服务不足的圣华金河谷地区招募、留住和培训STEM领域的学生。这项研究将为研究生和博士后提供培训，并影响到多个领域，包括活性物质物理、细胞生物学和组织工程，以及生物启发的软材料设计。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。

NONTECHNICAL SUMMARYThis CAREER award supports theoretical and computational research to describe and understand the behavior of biologically inspired active solids. The models developed in this research are motivated by mechanical force-driven shape changes in living matter occurring in the cell cytoskeleton and multicellular tissues. Living matter utilizes chemically patterned mechanical forces to change shape in programmed and robust ways during crucial biological processes such as tissue development and cell migration. They are thus excellent examples of active matter which comprise microscopic components that consume energy to generate mechanical forces and motion. Unlike active fluids where constituent components move freely, biological materials typically contain connected networks of polymers that respond to mechanical force by deforming like elastic springs. Further, unlike ordinary solids that deform under externally applied forces to reach a well-defined minimal energy state, the force-generating units of active solids are embedded within the material itself and can be redistributed by the deformations that they themselves generate. These unique features enable active solids to autonomously generate patterns and shapes not found in ordinary solids under thermodynamic equilibrium. The PI and his research team will create theoretical and computational models of shape-changing active solids by combining mechanical and chemical factors. The general aim is to theoretically and computationally investigate the unique shape changes and self-organization phenomena that are possible in active solids. The results will be compared with experimental data on cytoskeletal materials and blood clots obtained from the PI’s collaborators. Our research will provide fundamental understanding of self-organization in cell biology and tissue morphogenesis. It may influence strategies in tissue engineering as well as the design of synthetic soft materials capable of autonomous shape change. Education and outreach activities are integrated with this research. These center on creating unique interdisciplinary learning opportunities involving computation for students at multiple levels. The PI will (1) deliver summer computational workshops to high school students; (2) develop computational modules for the introductory physics classes for life science majors as well as core physics classes; and (3) train beginning graduate students in scientific computing basics through a summer bridge module. These educational and outreach efforts will help recruit and train the future STEM workforce in the underserved San Joaquin Valley of California and beyond. TECHNICAL SUMMARYThis CAREER award supports the development of a physical theory of spontaneous shape change and self-organization in elastic active matter through biologically inspired mechano-chemical feedback. It also supports the PI’s educational initiative to train students at multiple levels in scientific computation through interdisciplinary biophysical models. Active matter refers to collections of entities that consume chemical energy and generate mechanical forces and motion. In contrast to active fluids that contain self-propelling particles, active solids comprise constituents connected via elastic spring-like constraints that exhibit deformations instead of large-scale flows in response to mechanical force. In living matter, these mechanical forces are generated by molecular motors whose activity is patterned by chemical signals. The research will be inspired by the inherently mechano-chemical nature of living matter occurring both in the cell cytoskeleton and in multicellular tissue. The PI and his research team will develop a class of models combining active mechanical forces, elastic deformation, orientational order and chemical gradients, and their mutual interactions, leading to spontaneous shape change and pattern formation. The team of the PI will focus on two nonlinear mechanical systems that respond sensitively to mechanical forces: thin elastic shells that undergo 3D shape changes by buckling because of their inherent geometric nonlinearity, and disordered fiber networks that exhibit complex nonlinear deformation modes. Complementary modeling strategies will be used, including continuum models amenable to theoretical analysis, as well as discrete network models for numeric computation. The research will reveal how elastic deformations of living matter contribute to 1) the regulation of chemical concentration by geometry and strain; 2) mutual elastic interactions between active units driving their self-organization dynamics into ordered states; 3) long-range orientational order and associated topological defects through deformation-induced alignment, and 4) complex 3D shapes arising through various buckling instabilities. The PI proposes an integrated educational plan involving computational training at multiple levels, from K-12 to undergraduate and graduate students. This will be delivered through 1) summer computational workshops and demonstrations designed for K-12 school students; 2) computational modules for the introductory physics classes for life science majors as well as core physics classes; and 3) training beginning graduate students through a summer bridge program on computational skills. These educational and outreach activities will contribute to the recruitment, retention, and training of students in STEM fields in the underserved San Joaquin Valley region of California. The research will provide training for a graduate student and a postdoc, and impact several fields including active matter physics, cell biology and tissue engineering, as well as bio-inspired soft materials design.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.