Improving Spectral, Spatial, and Mechanistic Resolution Using Fourier Transform Nonlinear Optics: A Tutorial Review

Megan A. Steves, Kenneth L. Knappenberger

Research output: Contribution to journalReview articlepeer-review

2 Scopus citations

Abstract

Fourier transform nonlinear optics (FT-NLO) is a powerful experimental physical chemistry tool that provides insightful spectroscopic and imaging data. FT-NLO has revealed key steps in both intramolecular and intermolecular energy flow. Using phase-stabilized pulse sequences, FT-NLO is employed to resolve coherence dynamics in molecules and nanoparticle colloids. Recent advances in time-domain NLO interferometry using collinear beam geometries makes determination of molecular and material linear and nonlinear excitation spectra, homogeneous line width, and nonlinear excitation pathways straightforward. When combined with optical microscopy, rapid acquisition of hyperspectral images with the information content of FT-NLO spectroscopy is possible. With FT-NLO microscopy, molecules and nanoparticles colocated within the optical diffraction limit can be distinguished based on their excitation spectra. The suitability of certain nonlinear signals for statistical localization present exciting prospects for using FT-NLO to visualize energy flow on chemically relevant length scales. In this tutorial review, descriptions of FT-NLO experimental implementations are provided along with theoretical formalisms for obtaining spectral information from time-domain data. Select case studies that illustrate the use of FT-NLO are presented. Finally, strategies for extending super-resolution imaging capabilities based on polarization-selective spectroscopy are offered.

Original languageEnglish (US)
Pages (from-to)130-142
Number of pages13
JournalACS Physical Chemistry Au
Volume3
Issue number2
DOIs
StatePublished - Mar 22 2023

All Science Journal Classification (ASJC) codes

  • Chemistry (miscellaneous)
  • Physical and Theoretical Chemistry
  • Computational Theory and Mathematics
  • Computer Science Applications

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