Directed Assembly of Nanoscale Process Systems

纳米级工艺系统的定向组装

• 批准号: 1033533
• 负责人: Paul Barton
• 金额: $ 50万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-15 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1033533&HistoricalAwards=false
• 关键词: Directed; Assembly; Nanoscale; Process; Systems

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.

1033533 Barton这项研究将开发概念设计工具，用于可靠地制造具有复杂，非周期性和一般非密集几何形状的纳米结构。自组装以前已经被用于从纳米颗粒构建块（例如胶体颗粒、金属颗粒和DNA）构建简单的周期性纳米结构（薄膜、表面上的2-D模板和3-D块状材料结构）。然而，目前不可能以足够的可靠性制造更复杂的、非周期性的和/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，以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。特别功能化的纳米粒子的自组装行为，目的是开发最佳的定向组装策略，实现所需产品的高产率。纳米颗粒（如DNA瓦片）的自组装动力学将使用主方程进行建模，该主方程考虑了形状，大小，旋转以及颗粒之间的短程和长程相互作用以及外部控制的影响：库仑相互作用，货车德瓦尔斯力，互补DNA碱基对的氢键等。一个多分辨率，自上而下的方法将减轻组合的模型，以易于处理的水平，使确定性的动态优化的主方程，以最大限度地提高所需的配置的最终概率。对于更大规模的问题，动态优化的基础上采样的主方程也将被考虑。新的算法也将被开发，以确定最可靠的方法制造一个复杂的纳米结构从？子组件。这些算法将确定纳米粒子功能化的最佳方式（如特定的DNA序列），以及一步一步的？食谱？用于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曲线，再次使所需产物的产率最大化。这些结果将适用于复杂的二维纳米结构和推广的许多类型的纳米粒子building blocks.Intellectual MeritThe概念设计工具，配方和方法，从这方面的努力，将使进步的能力，设计和可靠地制造纳米结构的广泛应用。通过在复杂、非周期性和非致密几何形状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朝着专用纳米结构的有用应用和商业化的方向发展。非周期性纳米结构的可靠制造将为广泛学科的新应用打开大门，包括纳米电子电路、分子计算、人造组织、纳米级化工厂、高灵敏度传感器、生物诊断学（蛋白质和DNA的检测），等离子体纳米颗粒波导和其它等离子体装置，人体组织机器接口，医疗装置，农业应用，更广泛的影响这项工作的结果将通过期刊文章、会议报告、公开分发的软件和课程大纲广泛传播。由此产生的模型、算法和软件将免费提供给科学界。将从麻省理工学院为这个项目挑选人员？它拥有多样化的研究生研究人员，成功地实现了高水平的少数民族和女性入学率。PI吸引了博士。学生来自许多民族背景和广泛的工程学科，包括化学，机械，环境和生物工程。麻省理工学院提供各种与研究相关的主题的高级课程，增强了多学科研究和教育的机会。