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

非技术总结这个职业奖支持理论和计算研究，以描述和理解生物启发的活性固体的行为。在这项研究中开发的模型是由机械力驱动的形状变化发生在细胞骨架和多细胞组织中的生命物质的动机。生物利用化学模式化的机械力，在组织发育和细胞迁移等关键生物过程中以程序化和稳健的方式改变形状。因此，它们是活性物质的极好例子，活性物质包括消耗能量以产生机械力和运动的微观成分。与组成成分自由移动的活性流体不同，生物材料通常包含连接的聚合物网络，这些聚合物网络通过像弹性弹簧一样变形来响应机械力。此外，与在外部施加的力下变形以达到明确定义的最小能量状态的普通固体不同，活性固体的力产生单元嵌入在材料本身中，并且可以通过它们自身产生的变形重新分布。这些独特的功能使活性固体能够在热力学平衡下自主生成普通固体中没有的图案和形状。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改变活性固体的理论和计算模型。总的目标是从理论和计算上研究活性固体中可能存在的独特形状变化和自组织现象。将结果与PI合作者获得的细胞骨架材料和血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。 教育和推广活动与这项研究相结合。这些中心创造独特的跨学科的学习机会，涉及多层次的学生计算。PI将（1）为高中生提供夏季计算研讨会;（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;（3）通过夏桥模块培训开始的研究生科学计算基础知识。这些教育和推广工作将有助于在服务不足的加州圣华金河谷及其他地区招募和培训未来的STEM劳动力。技术总结该职业奖支持通过生物启发的机械化学反馈在弹性活性物质中自发形状变化和自组织的物理理论的发展。它还支持PI的教育计划，通过跨学科的生物物理模型在多个层次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。与包含自推进颗粒的活性流体相比，活性固体包括经由弹性弹簧状约束连接的成分，其响应于机械力而呈现变形而不是大规模流动。在生命物质中，这些机械力是由分子马达产生的，分子马达的活动由化学信号模式化。这项研究将受到细胞骨架和多细胞组织中生物物质固有的机械化学性质的启发。PI和他的研究团队将开发一类模型，结合主动机械力，弹性变形，取向顺序和化学梯度，以及它们之间的相互作用，导致自发的形状变化和图案形成。PI团队将专注于两个对机械力敏感的非线性力学系统：薄弹性壳，由于其固有的几何非线性而通过屈曲进行3D形状变化，以及呈现复杂非线性变形模式的无序纤维网络。将使用补充建模策略，包括适合理论分析的连续模型，以及用于数值计算的离散网络模型。该研究将揭示生命物质的弹性变形如何有助于：1）通过几何和应变调节化学浓度; 2）活性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）通过变形诱导的对齐实现长程取向有序和相关的拓扑缺陷，以及4）通过各种屈曲不稳定性产生的复杂3D形状。 PI提出了一个综合教育计划，涉及从K-12到本科生和研究生的多个层次的计算培训。这将通过1）为K-12学校学生设计的夏季计算研讨会和演示; 2）生命科学专业的入门物理课程以及核心物理课程的计算模块;以及3）通过计算技能的夏桥计划培训开始研究生。这些教育和推广活动将有助于加州服务不足的圣华金谷地区STEM领域学生的招聘、保留和培训。该研究将为一名研究生和一名博士后提供培训，并影响多个领域，包括活性物质物理学，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价值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.