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Directed Assembly of Nanoscale Process Systems

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:
$50.0万
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
项目状态:
已结题
起止时间:
2010-09-15 至 2014-08-31

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中文摘要
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英文摘要
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.
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Advances in Global Dynamic Optimization
Global Dynamic Optimization
Convex Underestimators for Dynamic Optimization Problems
Formal Verification of Hybrid Systems Using Global Optimization
国内基金
海外基金
晶态桥联聚倍半硅氧烷的自导向组装(self-directed assembly)及其发光性能
  • 批准号:
    21171046
  • 项目类别:
    面上项目
  • 资助金额:
    55.0万元
  • 批准年份:
    2011
  • 负责人:
    李焕荣
  • 依托单位: