Directed Assembly of Nanoscale Process Systems

这项研究将开发概念设计工具，用于可靠地制造具有复杂、非周期和一般非密集几何结构的纳米级结构。自组装以前已经被用来从胶体粒子、金属粒子和DNA等纳米粒子构建简单的周期性纳米结构(薄膜、表面的2-D模板和3-D块体材料结构)。然而，目前还不可能以足够的可靠性制造更复杂的、非周期的和/或非致密的结构。我们的目标是探索新的配方、模型和算法，目的是开发一套概念设计工具来解决复杂纳米结构的可靠制造。这项工作将研究外部控制(如纳米电极、系统温度等)的影响。对特殊功能化纳米颗粒的自组装行为进行研究，目的是开发最优的定向组装策略，以实现所需产品的高产量。纳米粒子(如DNA瓷砖)的自组装动力学将使用主方程建模，该方程考虑了形状、大小、旋转以及粒子之间和外部控制之间的短期和远程相互作用的影响：库仑相互作用、范德华力、互补DNA碱基对的氢键等。多分辨率、自上而下的方法将模型的组合简化到易于处理的水平，从而实现主方程的确定性动态优化，以最大化所需配置的最终概率。对于较大规模的问题，还将考虑基于主方程采样的动态优化。还将开发新的算法，以确定从子组件制造复杂纳米结构的最可靠方法。这些算法将确定纳米颗粒应该功能化的最佳方式(例如使用特定的DNA序列)，以及循序渐进的配方？将这些纳米颗粒组装成最终的纳米结构。对于任何给定的纳米结构，算法还将确定外部控制的最佳动态轮廓，再次最大化所需产品的产量。这些结果将适用于复杂的二维纳米结构，并推广到许多类型的纳米颗粒构建块。智力价值由这一努力产生的概念设计工具、配方和方法将使设计和可靠制造纳米结构的能力取得进步，适用于广泛的应用。通过在复杂、非周期和非致密几何结构的可靠制造问题上取得重大进展，未来纳米材料研究的重点可以向专门的纳米结构的有用应用和更多的商业化迈进。非周期性纳米结构的可靠制造将为广泛的学科领域的新应用打开大门，包括纳米电子电路、分子计算、人造组织、纳米化工厂、高灵敏度传感器、生物诊断学(检测蛋白质和DNA)、等离子体纳米粒子波导和其他等离子体设备、人体组织机器接口、医疗设备、农业应用和许多其他。由此产生的模型、算法和软件将免费提供给科学界。这个项目的人员将从麻省理工学院S研究生的多元化人才库中挑选出来，这一人才库已经成功地实现了少数民族和女性的高水平入学。PI吸引了来自许多种族背景和广泛的工程学科的博士生，包括化学、机械、环境和生物工程。麻省理工学院提供了一系列与研究相关的主题的高级课程，增加了多学科研究和教育的机会。

1033533BartonThis research will develop conceptual design tools for the reliable fabrication of nanoscale structures with complex, non-periodic, and generally non-dense geometries. Self-assembly has been used previously to construct simple periodic nanostructures (thin films, 2-D templates on surfaces, and 3-D bulk materials structures) from nanoparticle building blocks such as colloidal particles, metal particles, and DNA. However, it is not presently possible to fabricate more complex, non-periodic and/or nondense structures with sufficient reliability. The goal here is to explore novel formulations, models and algorithms with the aim of developing a suite of conceptual design tools to address reliable fabrication of complex nanoscale structures.The work will study the influence of external controls (such as nanoelectrodes, the system temperature, etc.) on the self-assembly behavior of specially functionalized nanoparticles, with the aim of developing optimal directed-assembly strategies that achieve high yields of the desired product. The self-assembly dynamics of nanoparticles (such as DNA tiles) will be modeled using master equations which consider the impact of shape, size, rotation, and both short- and long-range interactions among the particles and with external controls: Coulombic interactions, Van der Waals forces, hydrogen bonding of complementary DNA base pairs, and others. A multi-resolution, top-down approach will mitigate the combinatorics of the model to tractable levels, enabling deterministic dynamic optimization of the master equation to maximize the final probability of the desired configuration. For larger-scale problems, dynamic optimization based on sampling of the master equation will also be considered.New algorithms will also be developed to determine the most reliable method for fabrication of a complex nanostructure from ?sub-assemblies.? These algorithms will determine the optimal way in which nanoparticles should be functionalized (such as with specific DNA sequences), as well as the step-by-step ?recipe? for the assembly of these nanoparticles into the final nanostructure. For any given nanostructure, the algorithms will also determine the optimal dynamic profiles for external controls, again to maximize the yield of the desired product. These results will be applicable to complex two-dimensional nanostructures and generalized for many types of nanoparticle building blocks.Intellectual MeritThe conceptual design tools, formulations and methods that result from this effort will enable advances in the ability to design and reliably fabricate nanostructures for a wide range of applications. By making significant headway in the problem of reliable fabrication of complex, nonperiodic, and non-dense geometries, the focus of future nanoscale materials research can advance toward useful applications of specialized nanostructures and increased commercialization. The reliable fabrication of non-periodic nanostructures will open the door for new applications in a broad range of disciplines including nanoelectronic circuitry, molecular computing, artificial tissues, nanoscale chemical plants, high-sensitivity sensors, biodiagnostics (detection of proteins and DNA), plasmonic nanoparticle waveguides and other plasmonic devices, human tissue machine interfaces, medical devices, agricultural applications, and many others.Broader ImpactThe results of this work will be broadly disseminated through journal articles, conference presentations, publicly distributed software, and course curricula. The resulting models, algorithms and software will be made freely available to the scientific community. Personnel will be selected for this project from MIT?s diverse pool of graduate student researchers, which has successfully achieved high levels of minority and female enrollment. The PIs attract Ph.D. students from many ethnic backgrounds and a broad range of engineering disciplines, including chemical, mechanical, environmental, and biological engineering. MIT offers a diverse range of advanced-level courses on topics relevant for the research, enhancing the opportunities for multi-disciplinary research and education.