EAPSI:EAPSI: Investigation of the Wrinkling and Buckling Behavior of Layered Soft Materials with Applications in the Developing Brain

在妊娠的第三个三个月，人类的大脑从一个基本光滑的表面演变成成人大脑特有的“皱纹”外观。 这是如何发生的，为什么有时会出错？ 几十年来，力学界一直对这些问题感兴趣，试图将大脑建模为一个薄的、僵硬的、不断生长的层（灰质），附着在一个厚的、柔软的层（白色物质）上。 然而，最近的力学测试显示，灰质实际上比底层的白色物质硬度略低，这对许多先前的模型和假设提出了挑战。 通过与中国北京清华大学的冯希乔博士（软薄膜的弯曲和屈曲方面的专家）的合作，该项目将探索在类似刚度的基底上薄生长层的行为。 根据这些最新的发现，这项研究将有助于更好地了解大脑的发育。对于软基底上的硬生长层，预计会形成正弦波，而软基底上的软层生长将导致褶皱与收缩谷。 波和折痕之间的过渡逐渐发生在脑组织的感兴趣区域。 使用分析和数值方法，本研究将探讨软层状材料的刚度比接近统一的行为。 将在有限元软件Abaqus中进行数值模拟，使用内置的线性扰动分析以及模拟体积增长的用户定义的材料模型。NSF EAPSI奖是与中国科技部合作资助的。

During the third trimester of gestation, the human brain evolves from having a mostly smooth surface to the characteristic 'wrinkled' appearance of the adult brain. How does this happen, and why does it sometimes go wrong? The mechanics community has been interested in these questions for decades, attempting to model the brain as a thin, stiff, growing layer (gray matter) attached to a thicker, softer layer (white matter). Recent mechanical tests, however, have revealed that gray matter is actually slightly less stiff than the underlying white matter, challenging many prior models and assumptions. Through collaboration with Dr. Feng Xi-Qiao of Tsinghua University in Beijing, China, an expert in the wrinkling and buckling of soft films, this project will explore the behavior of thin growing layers on substrates of a similar stiffness. This research will lead to a greater understanding of brain development in light of these recent findings.For a stiff growing layer on a soft substrate, the formation of sinusoidal waves is expected, while the growth of a soft layer on a stiffer substrate will lead to creases with pinched valleys. The transition between waves and creases happens gradually in the region of interest for brain tissue. Using both analytical and numerical approaches, this research will explore the behavior of soft layered materials with stiffness ratios close to unity. Numerical simulations will be performed in the finite element software Abaqus, using the built-in linear perturbation analysis as well as user-defined material models that simulate volumetric growth. This NSF EAPSI award is funded in collaboration with the Chinese Ministry of Science and Technology.