Excellence in Research: Development of High Resolution Coherent 2D Rovibrational Spectroscopy

卓越的研究：高分辨率相干二维旋转振动光谱的开发

• 批准号: 1832098
• 负责人: Peter Chen
• 金额: $ 49.99万
• 依托单位: Spelman College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1832098&HistoricalAwards=false
• 关键词: Excellence; Research; Development; Resolution; Coherent

Professor Peter Chen's research team at Spelman College is developing a new high resolution spectroscopic technique to study molecules in gaseous mixtures in real time. The new spectroscopic method Professor Chen works on monitors very small signal shifts caused by the change in a gas mixture. It could be useful in many different areas, such as studying combustion systems, materials synthesis processes, and catalysis. The resulting information could be used to discover and identify new species produced during chemical reactions and provide information needed to understand reaction mechanisms. Consequently, it can lead to improved ways to reduce pollution, improve efficiency, and lower costs for manufacturing, automobile transportation, energy production, etc. Professor Chen works closely with a group of undergraduate students at Spelman College and prepares them for graduate studies in the STEM fields. He in particular encourages African American women students in research by providing them with a stimulating, cutting-edge undergraduate research experience.The technique that is being developed is based upon a new high resolution form of coherent multidimensional spectroscopy that uses rovibrational resonances and nonparametric four wave mixing processes. The shift from electronic enhancements to vibrational enhancements makes it easier to detect all species present in the sample. Advantages for using new nonparametric techniques are explored. New methods are also being developed that use the resulting multidimensional patterns to distinguish among signals from different species while also providing information on their structures. Professor Chen has established a strong record of recruiting and involving undergraduate students, many from underrepresented minority groups, on his project.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

斯佩尔曼学院彼得·陈教授的研究团队正在开发一种新的高分辨率光谱技术来实时研究气体混合物中的分子。 陈教授的新光谱方法致力于监测由气体混合物变化引起的非常小的信号变化。 它可用于许多不同的领域，例如研究燃烧系统、材料合成过程和催化。 由此产生的信息可用于发现和识别化学反应过程中产生的新物种，并提供了解反应机制所需的信息。 因此，它可以带来减少污染、提高效率、降低制造、汽车运输、能源生产等成本的改进方法。陈教授与斯佩尔曼学院的一群本科生密切合作，为他们攻读研究生做好准备。 STEM 领域。 他特别鼓励非裔美国女学生进行研究，为她们提供刺激的、前沿的本科研究经验。正在开发的技术基于一种新的高分辨率形式的相干多维光谱，该光谱使用振动共振和非参数四波混合过程。从电子增强到振动增强的转变使得检测样品中存在的所有物种变得更加容易。 探讨了使用新的非参数技术的优点。 新方法也正在开发中，利用由此产生的多维模式来区分来自不同物种的信号，同时提供有关其结构的信息。 陈教授在其项目中招募和吸引本科生（其中许多来自代表性不足的少数群体）方面建立了良好的记录。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

High resolution two-dimensional infrared (HR-2DIR) spectroscopy of gas phase molecules

气相分子的高分辨率二维红外 (HR-2DIR) 光谱

• DOI: 10.1063/5.0109084
• 发表时间: 2022-11
• 期刊: The Journal of Chemical Physics
• 作者: Daniels, DeAunna A.;Wells, Thresa A.;Chen, Peter C.
• 通讯作者: Chen, Peter C.

Multidimensional Pattern Recognition in High-Resolution 2D and 3D Spectra of Gas-Phase Molecules

气相分子高分辨率 2D 和 3D 光谱中的多维模式识别

• DOI: 10.1021/acs.accounts.2c00637
• 发表时间: 2023-01
• 期刊: Accounts of Chemical Research
• 影响因子: 18.3
• 作者: Chen; Peter C.
• 通讯作者: Peter C.

Two-dimensional pattern recognition methods for rapidly recording and interpreting high resolution coherent three-dimensional spectra

快速记录和解释高分辨率相干三维光谱的二维模式识别方法

• DOI: 10.1063/5.0047926
• 发表时间: 2021-05
• 期刊: The Journal of Chemical Physics
• 作者: Wells, Thresa A.;Kwizera, Muhire H.;Chen, Sarah M.;Jemal, Nihal;Brown, Morgan D.;Chen, Peter C.
• 通讯作者: Chen, Peter C.

Proof and Use of the Method of Combination Differences for Analyzing High-Resolution Coherent Multidimensional Spectra

高分辨率相干多维光谱分析组合差分法的证明与应用

• DOI: 10.3390/math8010044
• 发表时间: 2020-01
• 期刊: Mathematics
• 影响因子: 2.4
• 作者: Chen, Peter C.;Ehme, Jeffrey
• 通讯作者: Ehme, Jeffrey