Realizing Hierarchically Ordered Porous Functional Materials from the Crystallization of Both Large-scale and Colloidal Particles

有序多孔材料有望在许多领域提高性能。这类材料通常是通过一种称为自组装的过程制造的，即宏观材料的组成部分自发地排列成所需的结构。纳米级有序材料的自组装最近引起了科学家和工程师的兴趣和想象，而更大尺度、中观和宏观尺度组件的自组装也会对组织工程、微电子、能源和3-D视觉显示产生巨大影响。然而，尽管有这些技术驱动因素，在这些更大规模的自组装还没有得到科学和工程界的关注，这一领域仍处于起步阶段。该奖项支持自组装方法的研究和开发，这些方法适用于制造有序的多孔材料，这些材料由比纳米材料大得多的构建块构成（即在几十到几百或微米的尺寸范围内）。除了将自组装方法引入全新的构建模块之外，该领域的成功项目还将允许将新技术与现有纳米级方法相结合，最终导致在前所未有的尺寸范围内有序制造材料。预计这类新材料将在组织工程（支架）、燃料电池/电池电极制造、制药等应用领域取得进展，因此，这项研究的结果将使美国经济和整个社会受益。这项研究结合了化学、物理、工程和材料科学方面的专业知识。多学科方法将有助于扩大代表性不足的群体在研究中的参与，并对工程教育产生积极影响。胶体结晶是纳米级粒子自组装的主要技术，然而，直到最近，这种技术在几微米以上的尺度上基本上没有使用过。这部分是由于这样一个事实，即在这些较大的中观和宏观尺度上，潜在的热效应（即布朗运动）足够小，以至于组成部分在非平衡状态下被动力学捕获。研究小组计划结合实验和建模（耦合离散元素和晶格玻尔兹曼方法），以进一步开发一系列有前途的新材料加工策略，利用最近发现的大尺度（10到100微米）稀释流体颗粒系统的不稳定性。理论和尺度上的争论将被用来确定诱发所需不稳定性的必要标准。这些新策略将打开颗粒结晶技术的颗粒尺寸范围，通常远远超出胶体极限。然后，现有（胶体）技术与新方法的结合可用于制造新的分层有序结构，模仿自然界中发现的结构（包括孔隙分布和化学计量），并最终形成新型材料加工方法的基础。

Ordered porous materials hold promise for enhanced performance in a variety of fields. Often this class of materials are fabricated through a process called self-assembly, whereby the component parts of a macroscopic material spontaneously arrange themselves into a desired structure. While self-assembly of materials that are ordered at the nano-scale has recently captured the interest and imagination of scientists and engineers, the self-assembly of larger, meso- and macro- scale components can also have a dramatic impact on tissue engineering, microelectronics, energy, and 3-D visual displays. Nevertheless, despite these technical drivers, self-assembly at these larger scales has received little focus from the scientific and engineering communities and this area remains in its infancy. This award supports the study and development of methods of self-assembly that are amenable to the fabrication of ordered porous materials constructed of building blocks that are considerably larger than nano-materials (that is, in the tens to hundreds or micrometer size range). In addition to opening the approach of self-assembly to a whole new range of building blocks, a successful project in this area will also allow a combination of the new techniques with existing nano-scale methods to ultimately lead to the fabrication of materials that are ordered over an unprecedented range of size scales. It is expected that this new class of materials can lead to advances in applications ranging from tissue engineering (scaffolds) to fuel cell/battery electrode fabrication to pharmaceuticals, thus, results from this research will benefit the U.S. economy and society as a whole. This research involves combining expertise in chemistry, physics, engineering, and materials science. The multi-disciplinary approach will help broaden participation of underrepresented groups in research and positively impact engineering education.Colloidal crystallization is a staple of nano-scale particle self-assembly, however, until recently is has been a technique that was essentially unused at scales beyond several microns. This is due, in part, to the fact that the underlying thermal effects (i.e., Brownian motion) at these larger meso- and macro- scales are small enough that components become kinetically arrested in non-equilibrium states. The research team plans to use a combination of experimentation and modeling (coupled Discrete Element and Lattice Boltzmann methods) in order to further develop a promising series of new materials processing strategies that exploit recently uncovered instabilities of dilute fluid-particle systems at large (10s to 100s of microns) scales. Theoretical and scaling arguments will be used to determine the criteria necessary to induce the required instabilities. These new strategies will open particle crystallization techniques to a range of particle sizes that are typically well beyond the colloidal limit. Then, a combination of existing (colloidal) techniques with the new approaches can be used to fabricate novel hierarchically-ordered structures that mimic those found in nature (both in pore distribution as well as stoichiometry) and can ultimately form the basis of novel materials processing methods.