异步和干涉非线性光谱学(AI-NS):拓展时间和光谱视野。

IF 2.9 2区 化学 Q3 CHEMISTRY, PHYSICAL The Journal of Physical Chemistry B Pub Date : 2025-02-20 Epub Date: 2025-02-07 DOI:10.1021/acs.jpcb.4c08228
Gi Rim Han, Hyunmin Jang, Tai Hyun Yoon, Minhaeng Cho
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引用次数: 0

摘要

自基于激光源精确频率技术的时间分辨光谱学出现以来,它已被认为是研究光化学系统动态过程的另一种方法。本文介绍了异步和干涉非线性光谱学(AI-NS),这是一种结合了异步产生的激光脉冲和干涉检测的光谱学技术,提供了前所未有的时间动态范围,具有高光谱分辨率和快速数据采集能力。通过消除对机械延迟阶段的需求,AI-NS有助于快速收集从飞秒到纳秒的时间分辨动态数据,同时区分频率相关的响应。在这里,我们详细介绍了AI-NS的技术方法,并探讨了其在各种系统研究中的应用,包括半导体和生物系统。此外,我们强调了未来的进展,如与多维光谱技术的集成。AI-NS不仅扩大了光谱分析的范围,而且为探索各种材料和分子系统开辟了新的途径。
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Asynchronous and Interferometric Nonlinear Spectroscopy (AI-NS): Expanding Temporal and Spectral Horizons.

Since the advent of time-resolved spectroscopy based on precision frequency technology of laser sources, it has been considered an alternative way to study dynamic processes in photochemical systems. This Perspective introduces asynchronous and interferometric nonlinear spectroscopy (AI-NS), a spectroscopic technique that combines asynchronously generated laser pulses and interferometric detection, offering an unprecedented temporal dynamic range with high spectral resolution and rapid data acquisition capabilities. By eliminating the need for mechanical delay stages, AI-NS facilitates the rapid collection of time-resolved data on dynamics ranging from femtoseconds to nanoseconds while simultaneously distinguishing frequency-dependent responses. Here, we detail the technical methodology of AI-NS and explore its applications to the studies of various systems, including semiconductors and biological systems. Additionally, we highlight prospective advancements, such as integration with multidimensional spectroscopy techniques. AI-NS not only expands the scope of spectroscopic analysis but also opens new avenues for the exploration of diverse materials and molecular systems.

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来源期刊
CiteScore
5.80
自引率
9.10%
发文量
965
审稿时长
1.6 months
期刊介绍: An essential criterion for acceptance of research articles in the journal is that they provide new physical insight. Please refer to the New Physical Insights virtual issue on what constitutes new physical insight. Manuscripts that are essentially reporting data or applications of data are, in general, not suitable for publication in JPC B.
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