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

斯佩尔曼学院的彼得·陈教授的研究团队正在开发一种新的高分辨率光谱技术，以实时研究气体混合物中的分子。新的光谱方法陈教授的工作是监测由气体混合物的变化引起的非常微小的信号漂移。它可以用于许多不同的领域，如研究燃烧系统、材料合成过程和催化。由此得到的信息可以用来发现和识别化学反应过程中产生的新物种，并提供了解反应机理所需的信息。因此，它可以改进减少污染、提高效率和降低制造、汽车运输、能源生产等成本的方法。陈教授与斯佩尔曼学院的一群本科生密切合作，为他们在STEM领域的研究生学习做准备。他特别鼓励非裔美国女性学生从事研究，为她们提供激励的、尖端的本科生研究体验。正在开发的技术基于一种新的高分辨率相干多维光谱学形式，它使用旋转共振和非参数四波混频过程。从电子增强到振动增强的转变使检测样品中存在的所有物种变得更容易。探讨了使用新的非参数技术的优点。还在开发新的方法，使用所产生的多维模式来区分来自不同物种的信号，同时还提供关于其结构的信息。陈教授在招募和吸收本科生参与他的项目方面有着良好的记录。这个奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.