DMREF: Collaborative Research: Strain Adaptive Materials

非技术描述：软机器人、可穿戴电子产品和个性化医疗的出现引发了对模仿活体组织机械反应的合成材料的需求。活体组织的独特之处在于它们触感柔软，但不易变形。这种应变适应性硬化代表了自然的防御机制之一，它可以防止意外的组织破裂，并注入一种特有的坚固感。探索了各种分子和宏观结构来再现组织力学；然而，它们无法在分子尺度上整合柔软和坚固。该项目旨在开发一种材料设计平台，该平台利用建筑代码对机械反应的巨大变化进行编程，从超软的脑组织到超紧致的皮肤。通过软物质理论家、合成化学家和实验物理学家的闭环合作，这种基于结构的设计方法将激发合成化学和软物质物理学的新方向，以创造具有编码结构-性质相关性的新型分子结构。与材料基因组计划的使命一致，这种方法将构成材料设计搜索引擎的基础，该引擎将指导和加速具有目标机械性能的组织复制品的合成。新型材料将催化许多技术的根本性转变，包括但不限于软机器人、主动伪装系统和生物医学设备。技术描述：传统的凝胶和弹性体不能复制组织的应变适应性硬化。变形时从超软到超硬的力学响应过渡需要不同结构基元的分层组织，从而触发不同应力水平下的级联变形机制。因此，该项目将解决三个基本且日益复杂的挑战。首先，理论建模将建立网络结构和机械性能（如刚度和硬度）之间的普遍相关性，并将形成定量指南，用于编码设计的聚合物系统中的精确机械“表型”。其次，将自组装部分引入网络结构代码将使聚合物组件具有应变自适应刚度。第三，动态交联的结合将赋予可编程的粘弹性响应，并将平台扩展到应变率响应的机械表型。项目目标的实现将产生一个分子代码，共同实现可编程和高效开发下一代具有应变和应变速率自适应机械性能的类组织合成材料。该奖项反映了美国国家科学基金会的法定使命，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。

Non-technical Description: The advent of soft robotics, wearable electronics, and personalized medicine has sparked a demand for synthetic materials that mimic the mechanical responses of living tissues. Living tissues are unique as they are soft at touch, yet resistant to deformation. This strain-adaptive stiffening represents one of Nature's defense mechanisms that prevents accidental tissue rupture and imbues a characteristic feeling of firmness. Various molecular and macroscopic constructs have been explored to reproduce the tissue mechanics; however, they fail to integrate softness and firmness on a molecular scale. This project aims at the development of a materials design platform that harnesses architectural codes for programming the grand variation of mechanical responses, ranging from that of ultra-soft brain tissue to super-firm skin. Through closed-loop collaboration of soft matter theoreticians, synthetic chemists, and experimental physicists, this design-by-architecture approach will inspire new directions in synthetic chemistry and soft-matter physics towards creation of novel molecular architectures with encoded structure-property correlations. In line with the mission of the Materials Genome Initiative, this approach will constitute the foundation for a materials design search engine that will guide and accelerate the synthesis of tissue replicas with targeted mechanical properties. The novel classes of materials will catalyze fundamental shifts in many technologies, including - but not limited to - soft robotics, active camouflage systems, and biomedical devices. Technical Description: Conventional gels and elastomers cannot replicate tissue's strain-adaptive stiffening. Transition from the super-soft to super-firm mechanical response upon deformation requires a hierarchical organization of different structural motifs that trigger a cascade of deformation mechanisms at different stress levels. As such, the project will address three fundamental and increasingly complex challenges. First, theoretical modeling will establish universal correlations between network architecture and mechanical properties such as stiffness and firmness, and will form quantitative guidelines for encoding precise mechanical "phenotypes" in designed polymeric systems. Second, introduction of self-assembling moieties into network architectural code will empower polymer assemblies with strain-adaptive stiffening. Third, incorporation of dynamic crosslinks will impart programmable viscoelastic response and extend the platform to strain-rate responsive mechanical phenotypes. Fulfillment of the project goals will yield a molecular code - collectively enabling the programmable and efficient development of next-generation of tissue-like synthetic materials with both strain- and strain rate-adaptive mechanical properties.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.