Computational Prediction of Mechanical and Transport Response Evolution in Degrading Porous Scaffolds

降解多孔支架中力学和传输响应演化的计算预测

• 批准号: 1537008
• 负责人: Francesco Costanzo
• 金额: $ 39.5万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-01 至 2019-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1537008&HistoricalAwards=false
• 关键词: Computational; Prediction; Mechanical; Transport; Response

Restoring living tissue functionality via tissue engineering is crucial for transformative advances in medicine. Tissue engineering materials must be biocompatible and often biodegradable in a controlled manner. For example, severed peripheral nerves can regrow, but new projections must be properly nourished and guided via tissue scaffolds. Scaffolds must have the right morphology for cell growth, the right transport properties for nourishing cells, and the right mechanical properties to stay compliant and integral during degradation and tissue regeneration. Biodegradable scaffolds are appealing because they need not be surgically removed; but they are effective only if degradation is synchronized with nerve regrowth. This is but one of many examples illustrating the extraordinary challenges in tissue engineering. This award will yield a multi-scale approach based on physics, mathematics, polymer chemistry, and image analysis to predict and interrogate evolving transport and mechanical properties of porous polymeric scaffolds during programmed enzymatic degradation. The contribution of the project to the advancement of mechanics is a new methodology to model, and thus understand, the behavior of multi-functional materials with evolving microstructure like those in nerve tissue engineering. An educational component is included to attract underrepresented minorities to engineering via level-appropriate workshops on applications of mechanics in neuroscience, and by involving undergraduates in the creation of coursework for courses in brain biomechanics.Biodegradable tissue engineering systems are deformable chemically-reacting porous mixtures with complex fluid-structure interaction. The project integrates specific existing averaging techniques with an original fluid-structure interaction approach to determine the coupled mechanical and transport properties of degrading porous polymer networks subjected to large deformation and mechanical loadings. The model system of relevance to the project is crosslinked urethane-doped polyester, a promising scaffold material for nerve regeneration with highly controllable porosity. This material will be modeled as a random polymer network. Samples will be analyzed via electron microscopy to quantify the network's morphology. Microscopic-level transport and mechanical properties will be determined via a statistical characterization of the polymer network structure. This process will define microstructurally accurate representative volume elements whose evolution can then be analyzed via a novel finite element fluid-structure interaction-based homogenization procedure for evolving microstructure due to degradation. This numerical scheme will yield effective mechanical and transport properties at the mesoscale as a function of degradation. A crucial advancement in mechanics is the framing of the homogenization problem as a fluid-structure interaction problem, by extending the immersed finite element method (a state-of-the-art fluid-structure interaction computational approach) to account for fluid flow through bodies with evolving microstructure. The project includes experiments to validate predicted properties. Material samples and full-scale scaffold at different stages of degradation will be characterized in terms of morphology, elastic moduli, and diffusivity, and these properties compared to corresponding numerical estimates.

通过组织工程恢复活组织功能对于医学的变革性进步至关重要。组织工程材料必须是生物相容的，并且通常以受控的方式生物降解。例如，切断的周围神经可以再生，但新的突起必须通过组织支架得到适当的营养和引导。 支架必须具有合适的细胞生长形态，合适的营养细胞运输特性，以及合适的机械特性，以在降解和组织再生过程中保持顺应性和完整性。 可生物降解的支架很有吸引力，因为它们不需要通过手术移除;但它们只有在降解与神经再生同步时才有效。 这只是许多例子之一，说明了组织工程的非凡挑战。该奖项将产生基于物理，数学，高分子化学和图像分析的多尺度方法，以预测和询问多孔聚合物支架在程序化酶降解过程中的运输和机械性能。该项目对力学进步的贡献是一种新的方法来建模，从而理解具有不断发展的微观结构的多功能材料的行为，如神经组织工程中的材料。 一个教育组成部分，包括吸引代表性不足的少数民族工程，通过适当的水平在神经科学中的应用力学讲习班，并通过参与本科生在脑生物mechanics.Biodegradable组织工程系统课程的课程创建可变形的化学反应多孔混合物与复杂的流体结构相互作用。该项目将现有的具体平均技术与原始的流体-结构相互作用方法相结合，以确定降解多孔聚合物网络在大变形和机械载荷下的耦合机械和传输特性。与该项目相关的模型系统是交联的掺杂聚醚的聚酯，这是一种具有高度可控孔隙率的有前途的神经再生支架材料。 该材料将被建模为随机聚合物网络。将通过电子显微镜分析样品以量化网络的形态。微观水平的运输和机械性能将通过聚合物网络结构的统计表征来确定。这个过程将定义微观结构上准确的代表性体积元素，其演变可以通过一种新的有限元流体-结构相互作用为基础的均匀化过程进行分析，由于退化的演变微观结构。这种数值方案将产生有效的机械和运输性能在中尺度作为退化的函数。力学的一个重要进步是将均匀化问题作为一个流体-结构相互作用问题，通过扩展浸入式有限元法（一种最先进的流体-结构相互作用计算方法）来考虑流体流过具有不断变化的微观结构的物体。该项目包括验证预测属性的实验。材料样品和全尺寸支架在不同阶段的降解将在形态，弹性模量和扩散率方面进行表征，并将这些属性与相应的数值估计进行比较。