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（纳米到微米尺度）颗粒的自组装和定向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例。 然而，创建具有可接受的小缺陷水平的目标结构的能力仍然缺乏;系统太容易在不期望的无序或缺陷丰富的状态中动态地被阻止。 我们的研究将协同联合收割机在数字显微成像技术和自由能计算方法的最新进展，以解决这个问题。 新兴的显微成像工具，包括技术，如共聚焦和全内反射，提供了前所未有的高分辨率，实时，三维可视化的胶体组装过程。 关键是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。 理论家传统上使用能量景观（EL）范式来处理这些问题，其中将数据从高维配置空间（阶数N，系统中的粒子数）映射到低维关键描述符集合中的EL。该EL是与感兴趣的过程的工程直接相关的量;它包含用于量化平衡状态和它们之间的过渡速率的信息（峰、谷、鞍）。 在这项研究中，我们将（1）开发一种数字光学显微镜实验和基于粒子的模拟之间的紧密耦合方法，以比较测量和预测的EL，以及（2）使用产生的EL进行工程设计。（设计、控制、优化）两个应用：光子晶体的自组装和电子纳米线器件的操作。尺寸在纳米到微米量级的颗粒浸入流体中，通常称为胶体，可以作为有趣的新产品的构建块。 例子包括光子带隙材料（例如，用于用光而不是电子操作的计算机）和动态可重构纳米线（例如，用于可调谐RF器件）。 在某些条件下，胶体颗粒将自发地组装成这种有用的材料，或者它们可以通过施加外部刺激如电场或温度梯度来诱导这样做。 然而，产生具有可接受的低水平缺陷的所需结构的途径还没有很好地理解。 这项研究采用了现代数字成像技术和统计力学领域的理论工具相结合，以测量，量化和控制装配过程。 我们将开发低缺陷结构化颗粒材料的工程途径的知识，这些材料可以在未来的制造过程中系统地实施。 此外，我们将使用实验（例如图像，视频），模拟（例如渲染，动画）和分析（例如动态，多维图）中生成的丰富视觉数据，为各级学生（K研究生）提供直观的教育体验，并在推广计划中向公众推广。