Laser Spectroscopy of Isolated Molecules and Systems: Structure, Dynamics and Analysis

孤立分子和系统的激光光谱：结构、动力学和分析

• 批准号: 312481-2013
• 负责人: Grant, EdwardR
• 金额: $ 5.03万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=632436
• 关键词: Laser; Spectroscopy; Isolated; Molecules; Systems

This proposal requests support to renew a Discovery Grant program that has made substantial progress in two areas of fundamental focus. (1) In work at an important interdisciplinary frontier between chemistry and physics, we have developed a novel supersonic beam methodology that employs pulsed lasers in multiresonant excitation sequences to create a quantum-state-selected frozen molecular Rydberg gas. This gas evolves to form a strongly coupled ultracold plasma. (2) Combining laser spectroscopy with multivariate signal processing, we have devised novel optical instrumentation and discerning interpretive tools that promise broad utility for the spectrochemical analysis and classification of complex materials. We now propose a program of pioneering new experiments and theoretical models in our ultracold plasma research that will use radiative emission and tomographic imaging to chart electronically nonadiabatic channels of intramolecular relaxation, and characterize the inelastic scattering dynamics by which the relaxation to the ultracold plasma state occurs. These measurements will create an unprecedented laboratory for the study of long-range collision physics in correlated many-body systems, with direct relevance to important questions concerned with warm dense matter, non-Fermi metals, coupled quantum wells and the technological production of high-brightness electron sources. We propose to advance significantly in our work at the frontier of analytical Raman and infrared spectroscopy by coupling novel instrument configurations to powerful new data mining and multivariate analysis strategies, with an eye to the classification of complex synthetic and biological materials. We will use machine learning strategies to draw telling characteristics from multivariate covariance models that link spectra to structural and functional properties. By means of target-directed feature selection, we will isolate signature sub-spectra that describe fundamental chemical variations responsible for excursions in the properties of complex materials. This research will yield new real-time spectrochemical classification methodologies with important analytical applications ranging from discerning industrial process-control to clinical diagnosis.

该提案要求支持更新在两个基本重点领域取得实质性进展的发现补助金计划。(1)在化学和物理学之间的一个重要的跨学科前沿的工作中，我们开发了一种新的超声束方法，该方法采用多共振激发序列中的脉冲激光来创建量子态选择的冷冻分子里德伯气体。这种气体演化形成强耦合的超冷等离子体。(2)结合激光光谱与多元信号处理，我们已经设计出新颖的光学仪器和识别的解释工具，承诺光谱化学分析和分类的复杂材料的广泛用途。我们现在提出了一个新的实验和理论模型，在我们的超冷等离子体研究，将使用辐射发射和断层成像图表电子非绝热通道的分子内弛豫，并表征非弹性散射动力学的超冷等离子体状态的松弛发生的程序。这些测量将建立一个前所未有的实验室，用于研究相关多体系统中的远程碰撞物理学，直接涉及与热致密物质、非费米金属、耦合量子威尔斯和高亮度电子源的技术生产有关的重要问题。我们建议通过将新的仪器配置与强大的新数据挖掘和多变量分析策略相结合，在分析拉曼和红外光谱的前沿工作中显着推进，着眼于复杂合成和生物材料的分类。我们将使用机器学习策略从将光谱与结构和功能特性联系起来的多元协方差模型中提取有说服力的特征。通过目标导向的特征选择，我们将分离出描述复杂材料特性偏移的基本化学变化的特征子光谱。这项研究将产生新的实时光谱化学分类方法，具有重要的分析应用，从识别工业过程控制到临床诊断。