Mesoscale modeling of Controlled Degradation and Erosion of Polymer Networks

该奖项支持开发一个计算框架，该框架在中尺度上捕获聚合物网络的受控降解。 了解和控制聚合物网络的降解在从伤口敷料和组织粘合剂到药物递送和神经网络生长调节的众多应用中起着至关重要的作用。特别令人感兴趣的是光诱导降解，其潜在的空间解决的物理和化学性质的降解聚合物材料的控制。目前的模型，通常是分析和连续的方法，告知我们的聚合物网络降解的理解，专注于小或大的长度尺度。小尺度和大尺度分别达到单个原子的水平，并延伸到可见距离和可见距离以外。我们对中间长度尺度的理解，从几纳米到几十或几百微米，被称为中尺度，仍然有限。 一个有效的计算方法的发展，预计在介观尺度上的降解聚合物网络的动力学建模推进基本的理解，并帮助建立可降解材料的有效设计的指导方针。该项目包括为研究生和本科生提供充足的研究和教育机会;重点将放在从代表性不足的群体中招收学生。一些研究成果将被纳入PI教授的课程，相关的教育材料将通过计算纳米技术网络的一部分科学和工程网关提供。该奖项支持开发一个计算建模框架，该框架在中尺度上捕获聚合物网络的光控降解。一个合适的耗散粒子动力学方法捕获侵蚀，反向凝胶化，和降解网络的弹性将被开发和验证。为了建立一个可靠的降解模型，将使用修改的节段排斥势来防止键合聚合物链的非物理拓扑交叉。作为一个模型系统，水凝胶形成的四臂聚乙二醇（PEG）大分子前体，通常被称为四-PEG凝胶的末端连接，选择。四臂PEG前体可以在其合成期间通过包括可光裂解的官能团来修饰，以实现受控的降解。所提出的模型的适用性可以扩展到各种网络架构，并用于研究他们的行为在外部施加的条件下。为了证明所开发的介观尺度方法的实用性，它将被用来捕获受控降解对纳米凝胶颗粒在液-液界面处的扩散和重建的影响。还将开发凝胶降解早期阶段的原始多尺度模型，其中中尺度模型将有效地按比例放大到相应的连续模型。 开发一种有效的计算方法来模拟降解聚合物网络的动力学，将通过考虑网络结构、所有相关物种的扩散、流体动力学相互作用、网络异质性和由溶剂质量局部控制的反应速率常数的细节来推进基础知识。建议的模拟方法将允许探测相关网络理论在中尺度的适用性，并可能建立未来设计的新型降解材料的动态和空间控制性能的指导方针。该项目将培训研究生和本科生，并支持多样性。研究成果将被纳入PI教授的课程中，相关的教育材料将通过NanoHub门户网站提供。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 SUMMARY This award supports the development of a computational framework that captures the controlled degradation of polymer networks at the mesoscale. Understanding and controlling degradation of polymer networks plays a vital role in a multitude of applications from wound dressings and tissue adhesives to the delivery of drugs and the growth regulation of neural networks. Of particular interest is light-induced degradation with its potential to spatially resolve the control over physical and chemical properties of degrading polymeric materials. Current models, often analytic and continuum approaches that inform our understanding of polymer network degradation, focus on small or large length scales. Small and large length scales reach down to the level of individual atoms and extend to and beyond visible distances, respectively. Our understanding on intermediate length scales, from a few nanometers to tens or hundreds of micrometers that are known as the mesoscale, remains limited. The development of an efficient computational approach for modeling the dynamics of degrading polymer networks on the mesoscale is expected to advance fundamental understanding and help establish guidelines for efficient design of degradable materials. The project includes ample research and educational opportunities for graduate and undergraduate students; strong emphasis will be placed on recruiting students from underrepresented groups. Some of the outcomes of the research will be incorporated into courses taught by the PI, and relevant educational materials will be made available via a science and engineering gateway that is part of the Network for Computational Nanotechnology. TECHNICAL SUMMARY This award supports the development of a computational modeling framework that captures photo-controlled degradation of polymer networks at the mesoscale. A suitable Dissipative Particle Dynamics approach capturing erosion, reverse gelation, and elasticity of the degrading network will be developed and validated. To establish a reliable model of degradation, a modified Segmental Repulsive Potential will be used to prevent unphysical topological crossings of bonded polymer chains. As a model system, hydrogels formed by the end-linking of four-arm polyethylene glycol (PEG) macromolecular precursors, often referred to as tetra-PEG gels, are chosen. The four-arm PEG precursors can be modified during their synthesis by including photocleavable functional groups to enable controlled degradation. The applicability of the proposed model can be extended to various network architectures and used to study their behavior under externally imposed conditions. To demonstrate the utility of the developed mesoscale approach, it will be used to capture the effects of controlled degradation on spreading and reconstruction of nanogel particles at liquid-liquid interfaces. An original multiscale model of early stages of gel degradation will also be developed, where the mesoscale model will be effectively scaled up into the respective continuum model. The development of an efficient computational approach for modeling the dynamics of degrading polymer networks will advance fundamental knowledge by accounting for the specifics of network architecture, diffusion of all the involved species, hydrodynamic interactions, network heterogeneities, and reaction rate constants that are locally controlled by the solvent quality. Proposed simulation methods will allow to probe the applicability of relevant network theories at the mesoscale and may establish guidelines for future design of novel degrading materials with dynamically and spatially controlled properties. This project will train graduate and undergraduate students and support diversity. Research outcomes will be incorporated into courses taught by the PI, and relevant educational materials will be made available through the NanoHub portal.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.