Time-Resolved EELS of Photonic Crystals and Glasses
Time-Resolved EELS of Photonic Crystals and Glasses
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
中文摘要
非技术描述:主要由Ge、As、S、Se和Te(硫属化物)组成的玻璃构成了一类重要的光学材料,其可以潜在地实现广泛的现代技术,包括光子学、电信、传感器和存储器件。然而,为这些技术应用定制的具有优化性能的硫属化物的成功成分设计需要制定准确的预测模型,这反过来又需要这些材料的原子结构和动力学的基础数据。 该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。这些结果将用于制定和测试模型,将微观结构和动力学与宏观性能联系起来,这将在这些材料的智能成分工程中发挥关键作用。 在这个研究计划的学生将学习调查的问题,在“基础科学”领域的基础工业应用。 在阿贡国家实验室(ANL)的实验设施的使用将丰富研究生教育和培训的经验,通过参与一个独特的研究环境,并将促进知识交流。该计划将与校园内代表性不足的少数民族服务和K-12外展计划协调,以吸引和招募代表性不足的研究生,并提高学生对玻璃材料科学和技术的认识。 技术规格:该计划旨在研究Ge-As-S-Se-Te系统中复杂硫系玻璃中玻璃转变(Tg)附近的传输和弛豫的结构机制的结构-性能关系,并开发原子尺度的理解。 中子/X射线衍射和反向蒙特卡罗建模的组合将用于首次获得这些材料的中程原子结构的异常完整的图片。 温度引起的结构变化和在这些玻璃和母液的结构物种之间的交换动力学的特点是在原位与77 Se和125 Te核磁共振(NMR)光谱在温度接近和高于Tg,和异位,样品与不同的时间-温度的历史相结合的NMR和拉曼光谱技术。 这些结果将用于开发预测模型,将原子结构和动力学与宏观物理性质联系起来,这对于这些材料的成分优化至关重要,可用于广泛的技术应用。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重要培训。
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.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
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
-
批准号:2141781
-
项目类别:Continuing Grant
-
资助金额:$50.0万
-
财政年份:2022
-
负责人:Nan Jiang
-
依托单位:
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:
CAREER: Probing Chemistry of Surface-Supported Nanostructures at the Angstrom-Scale
-
批准号:1944796
-
项目类别:Continuing Grant
-
资助金额:$68.61万
-
财政年份:2020
-
负责人:Nan Jiang
-
依托单位:
Collaborative Research: Integrated Experimental and Computational Studies for Understanding the Interplay of Photoreactive Materials and Persistent Contaminants
-
批准号:1807465
-
项目类别:Standard Grant
-
资助金额:$23.95万
-
财政年份:2018
-
负责人:Nan Jiang
-
依托单位:
Efficient Ensemble Methods for Predictive Fluid Flow Simulations Subject to Uncertainty
-
批准号:1720001
-
项目类别:Standard Grant
-
资助金额:$14.99万
-
财政年份:2017
-
负责人:Nan Jiang
-
依托单位:
海外基金