CDI-Type I: Collaborative Research: Cyber Enabled Engineering of Particle Based Materials and Devices using Energy Landscapes

CDI-I 型：协作研究：利用能源景观对基于粒子的材料和设备进行网络工程

• 批准号: 0835532
• 负责人: David Ford
• 金额: $ 24.79万
• 依托单位: University of Massachusetts Amherst
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-15 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0835532&HistoricalAwards=false
• 关键词: CDI; Type; Collaborative; Research; Cyber

The self- and directed- assembly of colloidal (nano- to micro- scale) particles into structures within materials and devices is an emerging paradigm with wide-ranging technological impact. However, the ability to create a target structure with an acceptably small level of defects is still lacking; systems too easily become dynamically arrested in undesired disordered, or defect-rich, states. Our research will synergistically combine recent advances in digital microscopic imaging techniques and free energy calculation methods to address this problem. Emerging microscopic imaging tools, including techniques such as confocal and total internal reflectance, provide unprecedented high-resolution, real-time, three-dimensional visualizations of colloidal assembly processes. The key is to mine the tremendous amount of digital data produced in these experiments to identify successful pathways to particle assembly. Theoreticians have traditionally approached such problems using the energy landscape (EL) paradigm, wherein one maps data from the high-dimensional configuration space (of order N, the number of particles in the system) to an EL in a low-dimensional set of key descriptors. This EL is the quantity of direct relevance to engineering of the process of interest; it contains the information (peaks, valleys, saddles) to quantify the equilibrium states and transition rates between them. In this research we will (1) develop a close coupling methodology between digital optical microscopy experiments and particle-based simulation to compare measured and predicted ELs, and (2) use the resulting ELs to engineer (design, control, optimize) two applications: the self-assembly of photonic crystals and operation of electronic nanowire devices.Particles with sizes on the order of nanometers to micrometers immersed in fluid, commonly called colloids, can serve as the building blocks of interesting new products. Examples include photonic band gap materials (e.g. for computers that operate with light instead of electrons) and dynamically reconfigurable nanowires (e.g. for tunable RF devices). Under certain conditions the colloidal particles will spontaneously assemble into such useful materials, or they can be induced to do so through the application of external stimuli such as electric fields or temperature gradients. However, the pathways to creating desired structures with acceptably low levels of defects are not well understood. This research employs a combination of modern digital imaging techniques and theoretical tools from the field of statistical mechanics to measure, quantify, and control the assembly process. We will develop knowledge of engineered pathways to low-defect structured particulate materials that can be systematically implemented in the manufacturing processes of the future. Furthermore, we will use the rich visual data generated in experiments (e.g. images, videos), simulations (e.g. renderings, animations), and analyses (e.g. dynamic, multi-dimensional plots) to provide intuitive educational experiences for students at all levels (K-postgraduate) and in outreach programs to the general public.

胶体（纳米至微型）颗粒的自我组装成材料和设备内的结构是具有广泛技术影响的新兴范式。 但是，仍然缺乏具有可接受的缺陷水平的目标结构的能力。系统在不良的无序或缺陷状态下也很容易动态捕捉。 我们的研究将协同结合数字微观成像技术的最新进展和解决此问题的自由能计算方法。 新兴的微观成像工具（包括共聚焦和总内部反射率）提供了前所未有的高分辨率，实时，三维胶体组装过程的可视化。 关键是要挖掘这些实验中产生的大量数字数据，以确定粒子组装的成功途径。 传统上，理论家使用能量景观（EL）范式解决了此类问题，其中一个绘制了从高维构造空间（n阶，系统中的粒子数）到EL中的数据，以低维的关键描述符。该EL是与感兴趣过程工程的直接相关性的数量；它包含信息（峰，山谷，马鞍），以量化它们之间的平衡状态和过渡速率。 In this research we will (1) develop a close coupling methodology between digital optical microscopy experiments and particle-based simulation to compare measured and predicted ELs, and (2) use the resulting ELs to engineer (design, control, optimize) two applications: the self-assembly of photonic crystals and operation of electronic nanowire devices.Particles with sizes on the order of nanometers to micrometers immersed in fluid, commonly called胶体可以用作有趣的新产品的基础。 示例包括光子带隙材料（例如，对于用光而不是电子运行的计算机）和动态重新配置的纳米线（例如，对于可调的RF设备）。 在某些条件下，胶体颗粒将自发地组装成这种有用的材料，或者可以通过应用外部刺激（例如电场或温度梯度）引起它们。 但是，创建具有低水平缺陷水平的所需结构的途径尚不清楚。 这项研究采用了现代数字成像技术和从统计力学领域的理论工具的组合来衡量，量化和控制组装过程。 我们将开发出工程途径的知识，以在未来的制造过程中系统地实施的低缺陷结构化颗粒物材料。 此外，我们将使用实验中生成的丰富视觉数据（例如图像，视频），仿真（例如渲染，动画）和分析（例如动态，多维情节）为各级学生（K-Postgradure）（K-Postgradure）以及向一般公众提供外来的学生提供直觉的教育体验。