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Scalable Nanomanufacturing of Reconfigurable Photonic Crystals

Scalable Nanomanufacturing of Reconfigurable Photonic Crystals
可重构光子晶体的可扩展纳米制造
批准号:
1562861
负责人:
Peng Jiang
金额:
$25.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-06-01 至 2020-12-31

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中文摘要
翻译
这项发明和晶体管的超大规模集成引发了微电子革命,几乎影响了我们日常生活的方方面面。随着已有50年历史的摩尔定律接近极限,科学家们现在正转向以光为信息载体。不幸的是,与我们操纵电子相比,我们在纳米体积中控制光的能力在许多方面都处于初级阶段。一种被称为光子晶体的新型光学材料可能是继续向全光集成电路发展的关键。然而,传统的纳米制造技术用于制备具有三维有序纳米结构的光子晶体,存在产量低、样品面积小和成本高的问题。通过将简单、快速、廉价的胶体自组装方法与新型形状记忆聚合物相结合,该项目将探索一种新的可扩展纳米制造方法,用于晶片规模生产具有可重构光学特性的光子晶体。这一跨学科研究将通过该大学的几个成功项目,紧密结合到课程开发、新的示范模块设计以及对代表性不足的高中生和本科生的培训中。尽管已经开发了各种胶体自组装技术,但这些自下而上的方法大多只适用于小批量、实验室规模的光子晶体生产。此外,具有固定微结构的自组装光子晶体只适用于制作无源纳米光学器件。智能形状记忆聚合物可以从结构稳定的暂态中记忆和恢复其永久形状,在开发有源光子晶体器件方面具有广阔的前景。不幸的是,现有的大多数形状记忆聚合物都是热响应性的,它们经历了需要热的形状记忆循环。该研究小组的目标是同时进行实验和理论研究,以解决当前胶体自组装和形状记忆聚合物技术面临的关键科学和工程障碍。原位纳米力学和机械变色测试,以及多物理力学有限元分析模拟,将有助于基本了解新型形状记忆聚合物的特殊形状恢复机制,这种聚合物能够实现非传统的全室温形状记忆循环。通过光学表征和有限元光学模拟,阐明了自组装光子晶体对刺激响应的微结构-光学性质关系。通过可伸缩的自下而上的纳米制造技术,可以制备出具有最佳晶体结构和多种可记忆光学状态的大面积大孔聚合物光子晶体。
英文摘要
The microelectronics revolution sparked by the invention and the very-large-scale integration of transistors has affected almost every aspect of our daily lives. As the 50-year-old Moore's law is approaching its limits, scientists are now turning to light as the information carrier. Unfortunately, our ability to control light in nanoscopic volumes is in many ways in its infancy, compared with how we can manipulate electrons. A new class of optical materials known as photonic crystals may hold the key to continued progress towards all-optical integrated circuits. However, traditional nanomanufacturing technologies for producing photonic crystals with three-dimensionally ordered nanostructures suffer from low throughput, small sample areas, and high cost. By integrating a simple, fast, and inexpensive colloidal self-assembly methodology with a new type of shape memory polymer, this project will explore a novel scalable nanomanufacturing approach for wafer-scale production of photonic crystals with reconfigurable optical properties. This interdisciplinary research will be closely integrated into curriculum development, new demonstration module design, and training of underrepresented high school and undergraduate students through a few successful programs at the university. Although various colloidal self-assembly technologies have been developed, most of these bottom-up approaches are only favorable for low volume, laboratory-scale production of photonic crystals. Moreover, self-assembled photonic crystals with fixed microstructures are only appropriate for fabricating passive nanooptical devices. Smart shape memory polymers that can memorize and recover their permanent shapes from structurally stable temporary sates are promising for developing active photonic crystal devices. Unfortunately, most of the existing shape memory polymers are thermoresponsive, and they suffer from heat-demanding shape memory cycles. The research team aims to conduct simultaneous experimental and theoretical investigations to address the key scientific and engineering barriers faced by the current colloidal self-assembly and shape memory polymer technologies. In-situ nanoscopic mechanical and mechanochromic tests, along with multiphysics mechanical finite element analysis simulations will facilitate the basic understanding of the unusual shape recovery mechanisms of the new type of shape memory polymer that enables unconventional all-room-temperature shape memory cycles. The stimuli-responsive microstructure-optical property relationship of the self-assembled photonic crystals will be elucidated by optical characterization and finite element optical simulations. Large-area macroporous polymer photonic crystals with optimal crystal structures and multiple memorizable optical states will be fabricated by the scalable bottom-up nanomanufacturing technology.
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CAREER: Compiler and Runtime Support for Sampled Sparse Computations on Heterogeneous Systems
  • 批准号:
    2338144
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $54.89万
  • 财政年份:
    2024
  • 负责人:
    Peng Jiang
  • 依托单位:
CSR: Small: A Fine-Grained Hierarchical Memory Management System for Applications with Dynamic Memory Demand on GPUs
  • 批准号:
    2311610
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $52.0万
  • 财政年份:
    2023
  • 负责人:
    Peng Jiang
  • 依托单位:
Collaborative Research: CSR: Medium: Towards A Unified Memory-centric Computing System with Cross-layer Support
  • 批准号:
    2310423
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $25.0万
  • 财政年份:
    2023
  • 负责人:
    Peng Jiang
  • 依托单位:
Collaborative Research: PPoSS: Planning: Towards an Integrated, Full-stack System for Memory-centric Computing
  • 批准号:
    2028825
  • 项目类别:
    Standard Grant
  • 资助金额:
    $6.45万
  • 财政年份:
    2021
  • 负责人:
    Peng Jiang
  • 依托单位:
海外基金