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Time-Resolved EELS of Photonic Crystals and Glasses

Time-Resolved EELS of Photonic Crystals and Glasses
光子晶体和玻璃的时间分辨 EELS
批准号:
0603993
负责人:
Nan Jiang
金额:
$52.07万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2006
资助国家:
美国
项目状态:
已结题
起止时间:
2006-07-15 至 2011-06-30

项目摘要

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中文摘要
翻译
非技术描述:玻璃主要由Ge、As、S、Se和Te(硫系化合物)组成,是一类重要的光学材料,可能使广泛的现代技术成为可能,包括光子学、电信、传感器和存储设备。然而,为这些技术应用量身定做的具有优化性能的硫系化合物的成功成分设计需要制定准确的预测模型,这反过来又需要关于这些材料的原子结构和动力学的基本数据。这项研究计划旨在使用最先进的实验和模拟方法来研究原子结构,并研究这些玻璃及其衍生液体中的动力学现象。这些结果将被用来建立和测试将微观结构和动力学与宏观性能联系起来的模型,这将在这些材料的智能组成工程中发挥关键作用。这个研究项目的学生将学习研究作为工业应用基础的“基础科学”领域中的问题。使用阿贡国家实验室(ANL)的实验设施将通过参与独特的研究环境丰富研究生教育和培训经验,并将促进智力交流。该计划将与校园中代表不足的少数族裔服务和K-12外联计划协调,以吸引和招收代表不足的研究生,并提高学生对玻璃材料科学和技术的认识。技术细节:本项目旨在研究Ge-As-S-Se-Te系统中复杂硫化物玻璃的结构-性质关系,并对玻璃转变(Tg)附近的结构输运和驰豫机制进行原子尺度的理解。结合中子/X射线衍射和反向蒙特卡罗模拟,将首次获得这些材料的中程原子结构的异常完整的图景。用~(77)Se和~(125)Te核磁共振(~(125)Te)谱在Tg附近和以上的温度下原位表征这些玻璃和母液中的温度诱导的结构变化和结构物种之间的交换动力学,并利用核磁共振和拉曼光谱技术在不同时间-温度历史的样品上原位和异地表征。这些结果将被用来开发预测模型,将原子结构和动力学与宏观物理性质联系起来,这对于这些材料在广泛的技术应用中的成分优化至关重要。这项工作包括对研究生进行最先进的光谱、衍射和模拟技术方面的大量培训。
英文摘要
NON-TECHNICAL DESCRIPTION: Glasses consisting primarily of Ge, As, S, Se and Te (chalcogenides) constitute an important class of optical materials that can potentially enable a wide range of modern technologies including photonics, telecommunication, sensors and memory devices. However, successful compositional design of chalcogenides with optimized properties tailored for these technological applications needs formulation of accurate predictive models, which in turn requires fundamental data on the atomic structure and dynamics of these materials. This research program aims to use state-of-the-art experimental and simulation methods to study the atomic structure and to investigate dynamical phenomena in these glasses and in the liquids from which they derive. These results will be used to formulate and test models linking the microscopic structure and dynamics with the macroscopic properties, which will play key role in smart compositional engineering of these materials. Students in this research program will learn to investigate problems in the realm of "basic science" that underlies industrial applications. The use of experimental facilities at the Argonne National Laboratory (ANL) will enrich the graduate education and training experience through participation in a unique research environment and will foster intellectual exchange. This program will coordinate with the underrepresented minority-serving and K-12 outreach programs on campus to attract and recruit underrepresented graduate students and to increase the awareness of students in the science and technology of glassy materials. TECHNICAL DETAILS: This program seeks to study the structure-property relationships and to develop an atomic scale understanding of the structural mechanisms of transport and relaxation near the glass transition (Tg) in complex chalcogenide glasses in the Ge-As-S-Se-Te system. A combination of neutron/x-ray diffraction and Reverse Monte Carlo modeling will be used to obtain an unusually complete picture of the intermediate-range atomic structures of these materials for the first time. The temperature induced structural changes and the dynamics of exchange among structural species in these glasses and parent liquids will be characterized in situ with 77Se and 125Te nuclear magnetic resonance (NMR) spectroscopy at temperatures near and above Tg, and ex situ, on samples with different time-temperature histories by a combination of NMR and Raman spectroscopic techniques. These results will be used to develop predictive models, linking the atomic structure and dynamics with macroscopic physical properties, which are crucial for compositional optimization of these materials for a wide range of technological applications. This work includes significant training of graduate students in state-of-the-art spectroscopic, diffraction and simulation techniques.
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CAREER: New Algorithms and Models for Turbulence in Incompressible Fluids
  • 批准号:
    2143331
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $46.28万
  • 财政年份:
    2022
  • 负责人:
    Nan Jiang
  • 依托单位:
CAREER: Theoretical Foundations of Offline Reinforcement Learning
Probing Local Structural and Chemical Properties of Atomically Thin Two-Dimensional Materials by Optical Scanning Tunneling Microscopy
  • 批准号:
    2211474
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $53.75万
  • 财政年份:
    2022
  • 负责人:
    Nan Jiang
  • 依托单位:
Efficient Ensemble Methods for Predictive Fluid Flow Simulations Subject to Uncertainty
  • 批准号:
    2120413
  • 项目类别:
    Standard Grant
  • 资助金额:
    $14.99万
  • 财政年份:
    2021
  • 负责人:
    Nan Jiang
  • 依托单位:
海外基金